completed all the folds

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 {
-    "_best_ema": "None",
+    "_best_ema": "0.8140983125280881",
     "batch_size": "2",
     "configuration_manager": "{'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 160, 128], 'median_image_size_in_voxels': [146.0, 194.0, 149.0], 'spacing': [1.0, 1.0, 1.0], 'normalization_schemes': ['ZScoreNormalization', 'ZScoreNormalization'], 'use_mask_for_norm': [True, True], 'UNet_class_name': 'PlainConvUNet', 'UNet_base_num_features': 32, 'n_conv_per_stage_encoder': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'num_pool_per_axis': [4, 5, 5], 'pool_op_kernel_sizes': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'conv_kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'unet_max_num_features': 320, '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}, 'batch_dice': False}",
     "configuration_name": "3d_fullres",
     "cudnn_version": 8902,
-    "current_epoch": "0",
-    "dataloader_train": "<nnunetv2.training.data_augmentation.custom_transforms.limited_length_multithreaded_augmenter.LimitedLenWrapper object at 0x7f59076e5e20>",
-    "dataloader_train.generator": "<nnunetv2.training.dataloading.data_loader_3d.nnUNetDataLoader3D object at 0x7f58e49f6fa0>",
+    "current_epoch": "550",
+    "dataloader_train": "<nnunetv2.training.data_augmentation.custom_transforms.limited_length_multithreaded_augmenter.LimitedLenWrapper object at 0x7f1634bb7d00>",
+    "dataloader_train.generator": "<nnunetv2.training.dataloading.data_loader_3d.nnUNetDataLoader3D object at 0x7f1634bb7d30>",
     "dataloader_train.num_processes": "12",
     "dataloader_train.transform": "Compose ( [SpatialTransform( independent_scale_for_each_axis = False, p_rot_per_sample = 0.2, p_scale_per_sample = 0.2, p_el_per_sample = 0, data_key = 'data', label_key = 'seg', patch_size = [112, 160, 128], patch_center_dist_from_border = None, do_elastic_deform = False, alpha = (0, 0), sigma = (0, 0), do_rotation = True, angle_x = (-0.5235987755982988, 0.5235987755982988), angle_y = (-0.5235987755982988, 0.5235987755982988), angle_z = (-0.5235987755982988, 0.5235987755982988), do_scale = True, scale = (0.7, 1.4), border_mode_data = 'constant', border_cval_data = 0, order_data = 3, border_mode_seg = 'constant', border_cval_seg = -1, order_seg = 1, random_crop = False, p_rot_per_axis = 1, p_independent_scale_per_axis = 1 ), GaussianNoiseTransform( p_per_sample = 0.1, data_key = 'data', noise_variance = (0, 0.1), p_per_channel = 1, per_channel = False ), GaussianBlurTransform( p_per_sample = 0.2, different_sigma_per_channel = True, p_per_channel = 0.5, data_key = 'data', blur_sigma = (0.5, 1.0), different_sigma_per_axis = False, p_isotropic = 0 ), BrightnessMultiplicativeTransform( p_per_sample = 0.15, data_key = 'data', multiplier_range = (0.75, 1.25), per_channel = True ), ContrastAugmentationTransform( p_per_sample = 0.15, data_key = 'data', contrast_range = (0.75, 1.25), preserve_range = True, per_channel = True, p_per_channel = 1 ), SimulateLowResolutionTransform( order_upsample = 3, order_downsample = 0, channels = None, per_channel = True, p_per_channel = 0.5, p_per_sample = 0.25, data_key = 'data', zoom_range = (0.5, 1), ignore_axes = None ), GammaTransform( p_per_sample = 0.1, retain_stats = True, per_channel = True, data_key = 'data', gamma_range = (0.7, 1.5), invert_image = True ), GammaTransform( p_per_sample = 0.3, retain_stats = True, per_channel = True, data_key = 'data', gamma_range = (0.7, 1.5), invert_image = False ), MirrorTransform( p_per_sample = 1, data_key = 'data', label_key = 'seg', axes = (0, 1, 2) ), MaskTransform( apply_to_channels = [0, 1], seg_key = 'seg', data_key = 'data', set_outside_to = 0, mask_idx_in_seg = 0 ), RemoveLabelTransform( output_key = 'seg', input_key = 'seg', replace_with = 0, remove_label = -1 ), RenameTransform( delete_old = True, out_key = 'target', in_key = 'seg' ), DownsampleSegForDSTransform2( axes = None, output_key = 'target', input_key = 'target', order = 0, ds_scales = [[1.0, 1.0, 1.0], [0.5, 0.5, 0.5], [0.25, 0.25, 0.25], [0.125, 0.125, 0.125], [0.0625, 0.0625, 0.0625]] ), NumpyToTensor( keys = ['data', 'target'], cast_to = 'float' )] )",
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-    "dataloader_val.generator": "<nnunetv2.training.dataloading.data_loader_3d.nnUNetDataLoader3D object at 0x7f58e49f6f10>",
+    "dataloader_val": "<nnunetv2.training.data_augmentation.custom_transforms.limited_length_multithreaded_augmenter.LimitedLenWrapper object at 0x7f1634bb7c70>",
+    "dataloader_val.generator": "<nnunetv2.training.dataloading.data_loader_3d.nnUNetDataLoader3D object at 0x7f1634bb7a60>",
     "dataloader_val.num_processes": "6",
     "dataloader_val.transform": "Compose ( [RemoveLabelTransform( output_key = 'seg', input_key = 'seg', replace_with = 0, remove_label = -1 ), RenameTransform( delete_old = True, out_key = 'target', in_key = 'seg' ), DownsampleSegForDSTransform2( axes = None, output_key = 'target', input_key = 'target', order = 0, ds_scales = [[1.0, 1.0, 1.0], [0.5, 0.5, 0.5], [0.25, 0.25, 0.25], [0.125, 0.125, 0.125], [0.0625, 0.0625, 0.0625]] ), NumpyToTensor( keys = ['data', 'target'], cast_to = 'float' )] )",
     "dataset_json": "{'description': '', 'labels': {'background': 0, 'lesion': 1}, 'licence': 'hands off!', 'name': 'UCSF_Enhancement', 'numTraining': 961, 'reference': '', 'release': '0.0', 'channel_names': {'0': 'T1', '1': 'T1Post'}, 'file_ending': '.nii.gz'}",
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     "fold": "1",
     "folder_with_segs_from_previous_stage": "None",
     "gpu_name": "NVIDIA A100-SXM4-40GB",
-    "grad_scaler": "<torch.cuda.amp.grad_scaler.GradScaler object at 0x7f590d339280>",
+    "grad_scaler": "<torch.cuda.amp.grad_scaler.GradScaler object at 0x7f16387a9310>",
     "hostname": "anahita",
     "inference_allowed_mirroring_axes": "(0, 1, 2)",
     "initial_lr": "0.01",
     "is_cascaded": "False",
     "is_ddp": "False",
-    "label_manager": "<nnunetv2.utilities.label_handling.label_handling.LabelManager object at 0x7f590d339310>",
+    "label_manager": "<nnunetv2.utilities.label_handling.label_handling.LabelManager object at 0x7f16387a92e0>",
     "local_rank": "0",
-    "log_file": "/working/i2_phi3/CNS_lymphoma/repos/nnunet-2/nnUNet/nnunetv2/results/Dataset503_Enhancement/nnUNetTrainer__nnUNetPlans__3d_fullres/fold_1/training_log_2024_1_4_18_55_41.txt",
-    "logger": "<nnunetv2.training.logging.nnunet_logger.nnUNetLogger object at 0x7f590d339190>",
+    "log_file": "/working/i2_phi3/CNS_lymphoma/repos/nnunet-2/nnUNet/nnunetv2/results/Dataset503_Enhancement/nnUNetTrainer__nnUNetPlans__3d_fullres/fold_1/training_log_2024_1_23_12_23_45.txt",
+    "logger": "<nnunetv2.training.logging.nnunet_logger.nnUNetLogger object at 0x7f16387a9190>",
     "loss": "DeepSupervisionWrapper(\n  (loss): DC_and_CE_loss(\n    (ce): RobustCrossEntropyLoss()\n    (dc): MemoryEfficientSoftDiceLoss()\n  )\n)",
-    "lr_scheduler": "<nnunetv2.training.lr_scheduler.polylr.PolyLRScheduler object at 0x7f59076e5b80>",
+    "lr_scheduler": "<nnunetv2.training.lr_scheduler.polylr.PolyLRScheduler object at 0x7f1634c69b50>",
     "my_init_kwargs": "{'plans': {'dataset_name': 'Dataset503_Enhancement', 'plans_name': 'nnUNetPlans', 'original_median_spacing_after_transp': [1.0, 1.0, 1.0], 'original_median_shape_after_transp': [132, 194, 149], 'image_reader_writer': 'SimpleITKIO', 'transpose_forward': [0, 1, 2], 'transpose_backward': [0, 1, 2], 'configurations': {'2d': {'data_identifier': 'nnUNetPlans_2d', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 91, 'patch_size': [224, 160], 'median_image_size_in_voxels': [194.0, 149.0], 'spacing': [1.0, 1.0], 'normalization_schemes': ['ZScoreNormalization', 'ZScoreNormalization'], 'use_mask_for_norm': [True, True], 'UNet_class_name': 'PlainConvUNet', 'UNet_base_num_features': 32, 'n_conv_per_stage_encoder': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'num_pool_per_axis': [5, 5], 'pool_op_kernel_sizes': [[1, 1], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2]], 'conv_kernel_sizes': [[3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3]], 'unet_max_num_features': 512, '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}, 'batch_dice': True}, '3d_fullres': {'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 160, 128], 'median_image_size_in_voxels': [146.0, 194.0, 149.0], 'spacing': [1.0, 1.0, 1.0], 'normalization_schemes': ['ZScoreNormalization', 'ZScoreNormalization'], 'use_mask_for_norm': [True, True], 'UNet_class_name': 'PlainConvUNet', 'UNet_base_num_features': 32, 'n_conv_per_stage_encoder': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'num_pool_per_axis': [4, 5, 5], 'pool_op_kernel_sizes': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'conv_kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'unet_max_num_features': 320, '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}, 'batch_dice': False}}, 'experiment_planner_used': 'ExperimentPlanner', 'label_manager': 'LabelManager', 'foreground_intensity_properties_per_channel': {'0': {'max': 2047527.5, 'mean': 35477.049718847586, 'median': 1393.2421875, 'min': -32763.0, 'percentile_00_5': 103.0, 'percentile_99_5': 563834.0, 'std': 113955.12641145437}, '1': {'max': 3781445.75, 'mean': 82266.91961786283, 'median': 2449.01318359375, 'min': -32743.0, 'percentile_00_5': 219.0, 'percentile_99_5': 1595717.5, 'std': 273467.55908133776}}}, 'configuration': '3d_fullres', 'fold': 1, 'dataset_json': {'description': '', 'labels': {'background': 0, 'lesion': 1}, 'licence': 'hands off!', 'name': 'UCSF_Enhancement', 'numTraining': 961, 'reference': '', 'release': '0.0', 'channel_names': {'0': 'T1', '1': 'T1Post'}, 'file_ending': '.nii.gz'}, 'unpack_dataset': True, 'device': device(type='cuda')}",
     "network": "PlainConvUNet",
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     "output_folder": "/working/i2_phi3/CNS_lymphoma/repos/nnunet-2/nnUNet/nnunetv2/results/Dataset503_Enhancement/nnUNetTrainer__nnUNetPlans__3d_fullres/fold_1",
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     "oversample_foreground_percent": "0.33",

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+{
+    "_best_ema": "None",
+    "batch_size": "2",
+    "configuration_manager": "{'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 160, 128], 'median_image_size_in_voxels': [146.0, 194.0, 149.0], 'spacing': [1.0, 1.0, 1.0], 'normalization_schemes': ['ZScoreNormalization', 'ZScoreNormalization'], 'use_mask_for_norm': [True, True], 'UNet_class_name': 'PlainConvUNet', 'UNet_base_num_features': 32, 'n_conv_per_stage_encoder': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'num_pool_per_axis': [4, 5, 5], 'pool_op_kernel_sizes': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'conv_kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'unet_max_num_features': 320, '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}, 'batch_dice': False}",
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+    "cudnn_version": 8902,
+    "current_epoch": "0",
+    "dataloader_train": "<nnunetv2.training.data_augmentation.custom_transforms.limited_length_multithreaded_augmenter.LimitedLenWrapper object at 0x7f69f7f2ae20>",
+    "dataloader_train.generator": "<nnunetv2.training.dataloading.data_loader_3d.nnUNetDataLoader3D object at 0x7f69cf232f10>",
+    "dataloader_train.num_processes": "12",
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+    "dataset_json": "{'description': '', 'labels': {'background': 0, 'lesion': 1}, 'licence': 'hands off!', 'name': 'UCSF_Enhancement', 'numTraining': 961, 'reference': '', 'release': '0.0', 'channel_names': {'0': 'T1', '1': 'T1Post'}, 'file_ending': '.nii.gz'}",
+    "device": "cuda:0",
+    "disable_checkpointing": "False",
+    "enable_deep_supervision": "True",
+    "fold": "2",
+    "folder_with_segs_from_previous_stage": "None",
+    "gpu_name": "NVIDIA A100-SXM4-40GB",
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+    "hostname": "anahita",
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+    "preprocessed_dataset_folder_base": "/working/i2_phi3/CNS_lymphoma/repos/nnunet-2/nnUNet/nnunetv2/preprocessed/Dataset503_Enhancement",
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+    "cudnn_version": 8902,
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+    "dataloader_train": "<nnunetv2.training.data_augmentation.custom_transforms.limited_length_multithreaded_augmenter.LimitedLenWrapper object at 0x7fe00b275c70>",
+    "dataloader_train.generator": "<nnunetv2.training.dataloading.data_loader_3d.nnUNetDataLoader3D object at 0x7fe00b2519d0>",
+    "dataloader_train.num_processes": "12",
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+    "device": "cuda:0",
+    "disable_checkpointing": "False",
+    "enable_deep_supervision": "True",
+    "fold": "4",
+    "folder_with_segs_from_previous_stage": "None",
+    "gpu_name": "NVIDIA A100-SXM4-40GB",
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+    "hostname": "anahita",
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+    "local_rank": "0",
+    "log_file": "/working/i2_phi3/CNS_lymphoma/repos/nnunet-2/nnUNet/nnunetv2/results/Dataset503_Enhancement/nnUNetTrainer__nnUNetPlans__3d_fullres/fold_4/training_log_2024_1_15_09_18_12.txt",
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 {
-    "_best_ema": "None",
+    "_best_ema": "0.9101938028471865",
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     "configuration_manager": "{'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 160, 128], 'median_image_size_in_voxels': [117.0, 192.0, 160.0], 'spacing': [1.2000000476837158, 0.859375, 0.859375], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'UNet_class_name': 'PlainConvUNet', 'UNet_base_num_features': 32, 'n_conv_per_stage_encoder': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'num_pool_per_axis': [4, 5, 5], 'pool_op_kernel_sizes': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'conv_kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'unet_max_num_features': 320, '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}, 'batch_dice': False}",
     "configuration_name": "3d_fullres",
     "cudnn_version": 8902,
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-    "dataloader_train.generator": "<nnunetv2.training.dataloading.data_loader_3d.nnUNetDataLoader3D object at 0x7f44617aecd0>",
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     "dataloader_train.num_processes": "12",
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     "dataset_json": "{'description': '', 'labels': {'background': 0, 'CSF': 1, 'Cortical Gray Matter': 2, 'White Matter': 3, 'Gray Matter': 4, 'Brain Stem': 5, 'Cerebellum': 6}, 'licence': 'hands off!', 'name': 'pcnsl_tissue', 'numTraining': 67, 'reference': '', 'release': '0.0', 'channel_names': {'0': 'T1'}, 'file_ending': '.nii.gz'}",
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     "initial_lr": "0.01",
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     "is_ddp": "False",
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-    "logger": "<nnunetv2.training.logging.nnunet_logger.nnUNetLogger object at 0x7f4461b951c0>",
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+    "hostname": "anahita",
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+    "logger": "<nnunetv2.training.logging.nnunet_logger.nnUNetLogger object at 0x7f99179051c0>",
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+    "preprocessed_dataset_folder_base": "/working/i2_phi3/CNS_lymphoma/repos/nnunet-2/nnUNet/nnunetv2/preprocessed/Dataset504_Tissue",
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+    "torch_version": "2.1.2+cu121",
+    "unpack_dataset": "True",
+    "was_initialized": "True",
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+    "disable_checkpointing": "False",
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+    "network": "PlainConvUNet",
+    "num_epochs": "1000",
+    "num_input_channels": "1",
+    "num_iterations_per_epoch": "250",
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+    "preprocessed_dataset_folder_base": "/working/i2_phi3/CNS_lymphoma/repos/nnunet-2/nnUNet/nnunetv2/preprocessed/Dataset504_Tissue",
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+    "was_initialized": "True",
+    "weight_decay": "3e-05"
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+    "current_epoch": "0",
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+    "dataloader_train.num_processes": "12",
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+    "dataset_json": "{'description': '', 'labels': {'background': 0, 'CSF': 1, 'Cortical Gray Matter': 2, 'White Matter': 3, 'Gray Matter': 4, 'Brain Stem': 5, 'Cerebellum': 6}, 'licence': 'hands off!', 'name': 'pcnsl_tissue', 'numTraining': 67, 'reference': '', 'release': '0.0', 'channel_names': {'0': 'T1'}, 'file_ending': '.nii.gz'}",
+    "device": "cuda:0",
+    "disable_checkpointing": "False",
+    "enable_deep_supervision": "True",
+    "fold": "4",
+    "folder_with_segs_from_previous_stage": "None",
+    "gpu_name": "NVIDIA A100-SXM4-40GB",
+    "grad_scaler": "<torch.cuda.amp.grad_scaler.GradScaler object at 0x7f3abc81f280>",
+    "hostname": "anahita",
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+    "label_manager": "<nnunetv2.utilities.label_handling.label_handling.LabelManager object at 0x7f3abc81f340>",
+    "local_rank": "0",
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+    "network": "PlainConvUNet",
+    "num_epochs": "1000",
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+    "preprocessed_dataset_folder_base": "/working/i2_phi3/CNS_lymphoma/repos/nnunet-2/nnUNet/nnunetv2/preprocessed/Dataset504_Tissue",
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+}