diff --git a/MedNeXt_Base/fold_0_MRA/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/debug.json b/MedNeXt_Base/fold_0_MRA/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/debug.json
index db40d639bfedf2d52131f00789fc48217cd48a7d..a443e6f4dae62d2e156108835c47fcd3bee37c5b 100644
--- a/MedNeXt_Base/fold_0_MRA/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/debug.json
+++ b/MedNeXt_Base/fold_0_MRA/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/debug.json
@@ -1,28 +1,28 @@
 {
-    "all_tr_losses": "[]",
-    "all_val_eval_metrics": "[]",
-    "all_val_losses": "[]",
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+    "all_val_losses": "[np.float32(-0.13891171), np.float32(-0.18862052), np.float32(-0.27527642), np.float32(-0.4297609), np.float32(-0.54049027), np.float32(-0.54770553), np.float32(-0.58129156), np.float32(-0.5537441), np.float32(-0.6064613), np.float32(-0.5958266), np.float32(-0.5898377), np.float32(-0.58940816), np.float32(-0.6242577), np.float32(-0.6002115), np.float32(-0.6002398), np.float32(-0.64023215), np.float32(-0.6449814), np.float32(-0.5997826), np.float32(-0.64444697), np.float32(-0.648876), np.float32(-0.64477813), np.float32(-0.6378507), np.float32(-0.6434373), np.float32(-0.64476156), np.float32(-0.64833254), np.float32(-0.6455078), np.float32(-0.6556549), np.float32(-0.6378731), np.float32(-0.63279366), np.float32(-0.65044314), np.float32(-0.6294291), np.float32(-0.66389334), np.float32(-0.6640007), np.float32(-0.6616254), np.float32(-0.66669065), np.float32(-0.6777987), np.float32(-0.664281), np.float32(-0.6360865), np.float32(-0.63653404), np.float32(-0.6596195), np.float32(-0.6696193), np.float32(-0.57045805), np.float32(-0.66153586), np.float32(-0.6767838), np.float32(-0.6621902), np.float32(-0.6722601), np.float32(-0.6481445), np.float32(-0.6402954), np.float32(-0.6728914), np.float32(-0.6771526), np.float32(-0.6670751), np.float32(-0.6603112), np.float32(-0.6588047), np.float32(-0.66034734), np.float32(-0.68105817), np.float32(-0.6493907), np.float32(-0.67164636), np.float32(-0.6050971), np.float32(-0.6631946), np.float32(-0.6805749), np.float32(-0.6735513), np.float32(-0.67058146), np.float32(-0.67234206), np.float32(-0.66152483), np.float32(-0.6698024), np.float32(-0.65480924), np.float32(-0.6376995), np.float32(-0.6622743), np.float32(-0.67514414), np.float32(-0.6725996), np.float32(-0.68162555), np.float32(-0.68050635), np.float32(-0.68147206), np.float32(-0.6894269), np.float32(-0.68230134), np.float32(-0.6784141), np.float32(-0.689563), np.float32(-0.6798328), np.float32(-0.68488264), np.float32(-0.68433416), np.float32(-0.66806847), np.float32(-0.68567747), np.float32(-0.68608534), np.float32(-0.6657856), np.float32(-0.6806371), np.float32(-0.68522704), np.float32(-0.68429923), np.float32(-0.68005705), np.float32(-0.67855537), np.float32(-0.6744205), np.float32(-0.68231046), np.float32(-0.67377794), np.float32(-0.68710274), np.float32(-0.6731494), np.float32(-0.68342584), np.float32(-0.6979917), np.float32(-0.68674475), np.float32(-0.66333956), np.float32(-0.6848276), np.float32(-0.68224114), np.float32(-0.69371474), np.float32(-0.7029247), np.float32(-0.6758414), np.float32(-0.70015746), np.float32(-0.688315), np.float32(-0.69088334), np.float32(-0.660208), np.float32(-0.6822543), np.float32(-0.7015041), np.float32(-0.68673724), np.float32(-0.68340623), np.float32(-0.68413115), np.float32(-0.69866925), np.float32(-0.68427), np.float32(-0.6926604), np.float32(-0.6910901), np.float32(-0.68377435), np.float32(-0.6888629), np.float32(-0.692942), np.float32(-0.67623407), np.float32(-0.67599493), np.float32(-0.69530123), np.float32(-0.7065623), np.float32(-0.6856695), np.float32(-0.6901111), np.float32(-0.6906693), np.float32(-0.6999477), np.float32(-0.67912793), np.float32(-0.6855784), np.float32(-0.6732365), np.float32(-0.69205725), np.float32(-0.67903817), np.float32(-0.69364244), np.float32(-0.6824643), np.float32(-0.6838267), np.float32(-0.69457835), np.float32(-0.67736214), np.float32(-0.687075), np.float32(-0.69551116), np.float32(-0.6894928), np.float32(-0.6751489), np.float32(-0.693892), np.float32(-0.6657675), np.float32(-0.6983433), np.float32(-0.6920445), np.float32(-0.6920022), np.float32(-0.6987696), np.float32(-0.68133575), np.float32(-0.68630743), np.float32(-0.69681287)]",
     "all_val_losses_tr_mode": "[]",
     "also_val_in_tr_mode": "False",
-    "amp_grad_scaler": "None",
+    "amp_grad_scaler": "<torch.cuda.amp.grad_scaler.GradScaler object at 0x7f1c56ffcd70>",
     "base_num_features": "30",
     "basic_generator_patch_size": "[205 205 205]",
     "batch_dice": "False",
     "batch_size": "2",
-    "best_MA_tr_loss_for_patience": "None",
-    "best_epoch_based_on_MA_tr_loss": "None",
-    "best_val_eval_criterion_MA": "None",
+    "best_MA_tr_loss_for_patience": "-0.74407077",
+    "best_epoch_based_on_MA_tr_loss": "148",
+    "best_val_eval_criterion_MA": "0.59173995",
     "classes": "[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36]",
     "conv_per_stage": "2",
     "data_aug_params": "{'selected_data_channels': None, 'selected_seg_channels': [0], 'do_elastic': False, 'elastic_deform_alpha': (0.0, 900.0), 'elastic_deform_sigma': (9.0, 13.0), 'p_eldef': 0.2, 'do_scaling': True, 'scale_range': (0.7, 1.4), 'independent_scale_factor_for_each_axis': False, 'p_independent_scale_per_axis': 1, 'p_scale': 0.2, 'do_rotation': True, 'rotation_x': (-0.5235987755982988, 0.5235987755982988), 'rotation_y': (-0.5235987755982988, 0.5235987755982988), 'rotation_z': (-0.5235987755982988, 0.5235987755982988), 'rotation_p_per_axis': 1, 'p_rot': 0.2, 'random_crop': False, 'random_crop_dist_to_border': None, 'do_gamma': True, 'gamma_retain_stats': True, 'gamma_range': (0.7, 1.5), 'p_gamma': 0.3, 'do_mirror': True, 'mirror_axes': (0, 1, 2), 'dummy_2D': False, 'mask_was_used_for_normalization': OrderedDict({0: False}), 'border_mode_data': 'constant', 'all_segmentation_labels': None, 'move_last_seg_chanel_to_data': False, 'cascade_do_cascade_augmentations': False, 'cascade_random_binary_transform_p': 0.4, 'cascade_random_binary_transform_p_per_label': 1, 'cascade_random_binary_transform_size': (1, 8), 'cascade_remove_conn_comp_p': 0.2, 'cascade_remove_conn_comp_max_size_percent_threshold': 0.15, 'cascade_remove_conn_comp_fill_with_other_class_p': 0.0, 'do_additive_brightness': False, 'additive_brightness_p_per_sample': 0.15, 'additive_brightness_p_per_channel': 0.5, 'additive_brightness_mu': 0.0, 'additive_brightness_sigma': 0.1, 'num_threads': 8, 'num_cached_per_thread': 2, 'patch_size_for_spatialtransform': array([128, 128, 128])}",
     "dataset_directory": "/marimo/TopBrain2026/nnUNet_preprocessed/Task001_Brain2026",
     "deep_supervision_scales": "[[1, 1, 1], [np.float64(0.5), np.float64(0.5), np.float64(0.5)], [np.float64(0.25), np.float64(0.25), np.float64(0.25)], [np.float64(0.125), np.float64(0.125), np.float64(0.125)], [np.float64(0.0625), np.float64(0.0625), np.float64(0.0625)], [np.float64(0.03125), np.float64(0.03125), np.float64(0.03125)]]",
     "deterministic": "False",
-    "dl_tr": "<nnunet_mednext.training.dataloading.dataset_loading.DataLoader3D object at 0x7f45a6e45fd0>",
-    "dl_val": "<nnunet_mednext.training.dataloading.dataset_loading.DataLoader3D object at 0x7f45a6ed0f50>",
+    "dl_tr": "<nnunet_mednext.training.dataloading.dataset_loading.DataLoader3D object at 0x7f1c571ee270>",
+    "dl_val": "<nnunet_mednext.training.dataloading.dataset_loading.DataLoader3D object at 0x7f1c57020e10>",
     "do_dummy_2D_aug": "False",
     "ds_loss_weights": "[0.51612903 0.25806452 0.12903226 0.06451613 0.03225806 0.        ]",
-    "epoch": "0",
+    "epoch": "150",
     "experiment_name": "nnUNetTrainerV2_MedNeXt_B_kernel3",
     "fold": "0",
     "folder_with_preprocessed_data": "/marimo/TopBrain2026/nnUNet_preprocessed/Task001_Brain2026/nnUNetData_plans_v2.1_trgSp_1x1x1_stage0",
@@ -32,7 +32,7 @@
     "inference_pad_kwargs": "{'constant_values': 0}",
     "init_args": "('/marimo/TopBrain2026/nnUNet_preprocessed/Task001_Brain2026/nnUNetPlansv2.1_trgSp_1x1x1_plans_3D.pkl', 0, '/marimo/TopBrain2026/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1', '/marimo/TopBrain2026/nnUNet_preprocessed/Task001_Brain2026', False, 0, True, False, True)",
     "initial_lr": "0.001",
-    "log_file": "/marimo/TopBrain2026/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/training_log_2026_10_18_08_44_25.txt",
+    "log_file": "/marimo/TopBrain2026/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/training_log_2026_10_18_20_06_50.txt",
     "lr_scheduler": "None",
     "lr_scheduler_eps": "0.001",
     "lr_scheduler_patience": "30",
@@ -53,7 +53,7 @@
     "online_eval_fp": "[]",
     "online_eval_tp": "[]",
     "only_keep_largest_connected_component": "None",
-    "optimizer": "AdamW (\nParameter Group 0\n    amsgrad: False\n    betas: (0.9, 0.999)\n    capturable: False\n    decoupled_weight_decay: True\n    differentiable: False\n    eps: 0.0001\n    foreach: None\n    fused: None\n    lr: 0.001\n    maximize: False\n    weight_decay: 3e-05\n)",
+    "optimizer": "AdamW (\nParameter Group 0\n    amsgrad: False\n    betas: (0.9, 0.999)\n    capturable: False\n    decoupled_weight_decay: True\n    differentiable: False\n    eps: 0.0001\n    foreach: None\n    fused: None\n    lr: 0.0008639269723028191\n    maximize: False\n    weight_decay: 3e-05\n)",
     "output_folder": "/marimo/TopBrain2026/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0",
     "output_folder_base": "/marimo/TopBrain2026/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1",
     "oversample_foreground_percent": "0.33",
@@ -71,7 +71,7 @@
     "save_latest_only": "True",
     "stage": "0",
     "threeD": "True",
-    "tr_gen": "<batchgenerators.dataloading.multi_threaded_augmenter.MultiThreadedAugmenter object at 0x7f45a6e47620>",
+    "tr_gen": "<batchgenerators.dataloading.multi_threaded_augmenter.MultiThreadedAugmenter object at 0x7f1c571ef8c0>",
     "train_loss_MA": "None",
     "train_loss_MA_alpha": "0.93",
     "train_loss_MA_eps": "0.0005",
@@ -82,7 +82,7 @@
     "use_progress_bar": "False",
     "val_eval_criterion_MA": "None",
     "val_eval_criterion_alpha": "0.9",
-    "val_gen": "<batchgenerators.dataloading.multi_threaded_augmenter.MultiThreadedAugmenter object at 0x7f45a6ed1450>",
+    "val_gen": "<batchgenerators.dataloading.multi_threaded_augmenter.MultiThreadedAugmenter object at 0x7f1c57021bd0>",
     "was_initialized": "True",
     "weight_decay": "3e-05"
 }
\ No newline at end of file
diff --git a/MedNeXt_Base/fold_0_MRA/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/model_best.model b/MedNeXt_Base/fold_0_MRA/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/model_best.model
index aa47e562bff87448b23187fb82be032bbb472aa3..b6912cff37227697596fd0c0634e576a3ec2e7d5 100644
--- a/MedNeXt_Base/fold_0_MRA/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/model_best.model
+++ b/MedNeXt_Base/fold_0_MRA/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/model_best.model
@@ -1,3 +1,3 @@
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-oid sha256:0cba0354f0c6b7105481de5ec42ac93eef52fa9a049dcd7e716ea668caf2fc43
-size 127061506
+oid sha256:ca702214ecd1854bc592fcf4791ff729712710a12aa69d7015edd066ddd80632
+size 127089538
diff --git a/MedNeXt_Base/fold_0_MRA/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/model_latest.model b/MedNeXt_Base/fold_0_MRA/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/model_latest.model
index eff8e7c91acb06a0a6ec74fd2d757557a2c4a729..3c6dd209b15084032d6afe28750901eb6447cfe3 100644
--- a/MedNeXt_Base/fold_0_MRA/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/model_latest.model
+++ b/MedNeXt_Base/fold_0_MRA/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/model_latest.model
@@ -1,3 +1,3 @@
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-oid sha256:7ef73a26496cd00532be4b5c9bf0f5866e421740aa3d10a42b5198d7a307ced2
-size 127068208
+oid sha256:f8f7f2e6955fc6facb4ec147711f6af7e9c53cdc8fc455f606ad38c463d2c199
+size 127095024
diff --git a/MedNeXt_Base/fold_0_MRA/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/progress.png b/MedNeXt_Base/fold_0_MRA/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/progress.png
index 43590cb5b4328fb6f4f3cd9203d2b7e458d01c71..e37fda7eea893ab340942366c8ad08a3ed2e1682 100644
--- a/MedNeXt_Base/fold_0_MRA/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/progress.png
+++ b/MedNeXt_Base/fold_0_MRA/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/progress.png
@@ -1,3 +1,3 @@
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-oid sha256:3b829ed2007506fb1634325fb128e7b90e5a75de76fbee78533b7e6b8f9858d0
-size 274211
+oid sha256:b0e00f3401d06821c5d55d7a51dd72fbcda4e92f404dc317edc9e5940f6bbaf9
+size 310264
diff --git a/MedNeXt_Base/fold_0_MRA/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/training_log_2026_10_18_20_06_50.txt b/MedNeXt_Base/fold_0_MRA/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/training_log_2026_10_18_20_06_50.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4cad6d9e7059af140cff2a5980a369569b88ca61
--- /dev/null
+++ b/MedNeXt_Base/fold_0_MRA/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/training_log_2026_10_18_20_06_50.txt
@@ -0,0 +1,1736 @@
+Starting... 
+2026-10-18 20:06:50.428830: Using splits from existing split file: /marimo/TopBrain2026/nnUNet_preprocessed/Task001_Brain2026/splits_final.pkl 
+2026-10-18 20:06:50.429169: The split file contains 5 splits. 
+2026-10-18 20:06:50.429226: Desired fold for training: 0 
+2026-10-18 20:06:50.429276: This split has 20 training and 5 validation cases. 
+2026-10-18 20:06:51.237948: TRAINING KEYS:
+ odict_keys([np.str_('topcow_mr_001'), np.str_('topcow_mr_002'), np.str_('topcow_mr_003'), np.str_('topcow_mr_004'), np.str_('topcow_mr_005'), np.str_('topcow_mr_006'), np.str_('topcow_mr_007'), np.str_('topcow_mr_008'), np.str_('topcow_mr_011'), np.str_('topcow_mr_012'), np.str_('topcow_mr_013'), np.str_('topcow_mr_014'), np.str_('topcow_mr_016'), np.str_('topcow_mr_017'), np.str_('topcow_mr_020'), np.str_('topcow_mr_021'), np.str_('topcow_mr_023'), np.str_('topcow_mr_025'), np.str_('topcow_mr_026'), np.str_('topcow_mr_027')]) 
+2026-10-18 20:06:51.238338: VALIDATION KEYS:
+ odict_keys([np.str_('topcow_mr_010'), np.str_('topcow_mr_015'), np.str_('topcow_mr_018'), np.str_('topcow_mr_022'), np.str_('topcow_mr_024')]) 
+2026-10-18 20:06:52.823349: loading checkpoint /marimo/TopBrain2026/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_B_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/model_latest.model train= True 
+2026-10-18 20:06:52.974909: lr: 0.000864 
+2026-10-18 20:06:57.149177: Unable to plot network architecture: 
+2026-10-18 20:06:57.149513: No module named 'hiddenlayer' 
+2026-10-18 20:06:57.149826: 
+printing the network instead:
+ 
+2026-10-18 20:06:57.150055: MedNeXt(
+  (stem): Conv3d(1, 32, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+  (enc_block_0): Sequential(
+    (0): MedNeXtBlock(
+      (conv1): Conv3d(32, 32, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), groups=32)
+      (norm): GroupNorm(32, 32, eps=1e-05, affine=True)
+      (conv2): Conv3d(32, 64, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+      (act): GELU(approximate='none')
+      (conv3): Conv3d(64, 32, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    )
+    (1): MedNeXtBlock(
+      (conv1): Conv3d(32, 32, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), groups=32)
+      (norm): GroupNorm(32, 32, eps=1e-05, affine=True)
+      (conv2): Conv3d(32, 64, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+      (act): GELU(approximate='none')
+      (conv3): Conv3d(64, 32, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    )
+  )
+  (down_0): MedNeXtDownBlock(
+    (conv1): Conv3d(32, 32, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1), groups=32)
+    (norm): GroupNorm(32, 32, eps=1e-05, affine=True)
+    (conv2): Conv3d(32, 96, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    (act): GELU(approximate='none')
+    (conv3): Conv3d(96, 64, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    (res_conv): Conv3d(32, 64, kernel_size=(1, 1, 1), stride=(2, 2, 2))
+  )
+  (enc_block_1): Sequential(
+    (0): MedNeXtBlock(
+      (conv1): Conv3d(64, 64, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), groups=64)
+      (norm): GroupNorm(64, 64, eps=1e-05, affine=True)
+      (conv2): Conv3d(64, 192, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+      (act): GELU(approximate='none')
+      (conv3): Conv3d(192, 64, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    )
+    (1): MedNeXtBlock(
+      (conv1): Conv3d(64, 64, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), groups=64)
+      (norm): GroupNorm(64, 64, eps=1e-05, affine=True)
+      (conv2): Conv3d(64, 192, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+      (act): GELU(approximate='none')
+      (conv3): Conv3d(192, 64, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    )
+  )
+  (down_1): MedNeXtDownBlock(
+    (conv1): Conv3d(64, 64, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1), groups=64)
+    (norm): GroupNorm(64, 64, eps=1e-05, affine=True)
+    (conv2): Conv3d(64, 256, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    (act): GELU(approximate='none')
+    (conv3): Conv3d(256, 128, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    (res_conv): Conv3d(64, 128, kernel_size=(1, 1, 1), stride=(2, 2, 2))
+  )
+  (enc_block_2): Sequential(
+    (0): MedNeXtBlock(
+      (conv1): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), groups=128)
+      (norm): GroupNorm(128, 128, eps=1e-05, affine=True)
+      (conv2): Conv3d(128, 512, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+      (act): GELU(approximate='none')
+      (conv3): Conv3d(512, 128, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    )
+    (1): MedNeXtBlock(
+      (conv1): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), groups=128)
+      (norm): GroupNorm(128, 128, eps=1e-05, affine=True)
+      (conv2): Conv3d(128, 512, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+      (act): GELU(approximate='none')
+      (conv3): Conv3d(512, 128, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    )
+  )
+  (down_2): MedNeXtDownBlock(
+    (conv1): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1), groups=128)
+    (norm): GroupNorm(128, 128, eps=1e-05, affine=True)
+    (conv2): Conv3d(128, 512, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    (act): GELU(approximate='none')
+    (conv3): Conv3d(512, 256, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    (res_conv): Conv3d(128, 256, kernel_size=(1, 1, 1), stride=(2, 2, 2))
+  )
+  (enc_block_3): Sequential(
+    (0): MedNeXtBlock(
+      (conv1): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), groups=256)
+      (norm): GroupNorm(256, 256, eps=1e-05, affine=True)
+      (conv2): Conv3d(256, 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+      (act): GELU(approximate='none')
+      (conv3): Conv3d(1024, 256, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    )
+    (1): MedNeXtBlock(
+      (conv1): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), groups=256)
+      (norm): GroupNorm(256, 256, eps=1e-05, affine=True)
+      (conv2): Conv3d(256, 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+      (act): GELU(approximate='none')
+      (conv3): Conv3d(1024, 256, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    )
+  )
+  (down_3): MedNeXtDownBlock(
+    (conv1): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1), groups=256)
+    (norm): GroupNorm(256, 256, eps=1e-05, affine=True)
+    (conv2): Conv3d(256, 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    (act): GELU(approximate='none')
+    (conv3): Conv3d(1024, 512, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    (res_conv): Conv3d(256, 512, kernel_size=(1, 1, 1), stride=(2, 2, 2))
+  )
+  (bottleneck): Sequential(
+    (0): MedNeXtBlock(
+      (conv1): Conv3d(512, 512, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), groups=512)
+      (norm): GroupNorm(512, 512, eps=1e-05, affine=True)
+      (conv2): Conv3d(512, 2048, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+      (act): GELU(approximate='none')
+      (conv3): Conv3d(2048, 512, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    )
+    (1): MedNeXtBlock(
+      (conv1): Conv3d(512, 512, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), groups=512)
+      (norm): GroupNorm(512, 512, eps=1e-05, affine=True)
+      (conv2): Conv3d(512, 2048, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+      (act): GELU(approximate='none')
+      (conv3): Conv3d(2048, 512, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    )
+  )
+  (up_3): MedNeXtUpBlock(
+    (conv1): ConvTranspose3d(512, 512, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1), groups=512)
+    (norm): GroupNorm(512, 512, eps=1e-05, affine=True)
+    (conv2): Conv3d(512, 2048, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    (act): GELU(approximate='none')
+    (conv3): Conv3d(2048, 256, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    (res_conv): ConvTranspose3d(512, 256, kernel_size=(1, 1, 1), stride=(2, 2, 2))
+  )
+  (dec_block_3): Sequential(
+    (0): MedNeXtBlock(
+      (conv1): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), groups=256)
+      (norm): GroupNorm(256, 256, eps=1e-05, affine=True)
+      (conv2): Conv3d(256, 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+      (act): GELU(approximate='none')
+      (conv3): Conv3d(1024, 256, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    )
+    (1): MedNeXtBlock(
+      (conv1): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), groups=256)
+      (norm): GroupNorm(256, 256, eps=1e-05, affine=True)
+      (conv2): Conv3d(256, 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+      (act): GELU(approximate='none')
+      (conv3): Conv3d(1024, 256, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    )
+  )
+  (up_2): MedNeXtUpBlock(
+    (conv1): ConvTranspose3d(256, 256, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1), groups=256)
+    (norm): GroupNorm(256, 256, eps=1e-05, affine=True)
+    (conv2): Conv3d(256, 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    (act): GELU(approximate='none')
+    (conv3): Conv3d(1024, 128, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    (res_conv): ConvTranspose3d(256, 128, kernel_size=(1, 1, 1), stride=(2, 2, 2))
+  )
+  (dec_block_2): Sequential(
+    (0): MedNeXtBlock(
+      (conv1): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), groups=128)
+      (norm): GroupNorm(128, 128, eps=1e-05, affine=True)
+      (conv2): Conv3d(128, 512, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+      (act): GELU(approximate='none')
+      (conv3): Conv3d(512, 128, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    )
+    (1): MedNeXtBlock(
+      (conv1): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), groups=128)
+      (norm): GroupNorm(128, 128, eps=1e-05, affine=True)
+      (conv2): Conv3d(128, 512, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+      (act): GELU(approximate='none')
+      (conv3): Conv3d(512, 128, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    )
+  )
+  (up_1): MedNeXtUpBlock(
+    (conv1): ConvTranspose3d(128, 128, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1), groups=128)
+    (norm): GroupNorm(128, 128, eps=1e-05, affine=True)
+    (conv2): Conv3d(128, 384, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    (act): GELU(approximate='none')
+    (conv3): Conv3d(384, 64, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    (res_conv): ConvTranspose3d(128, 64, kernel_size=(1, 1, 1), stride=(2, 2, 2))
+  )
+  (dec_block_1): Sequential(
+    (0): MedNeXtBlock(
+      (conv1): Conv3d(64, 64, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), groups=64)
+      (norm): GroupNorm(64, 64, eps=1e-05, affine=True)
+      (conv2): Conv3d(64, 192, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+      (act): GELU(approximate='none')
+      (conv3): Conv3d(192, 64, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    )
+    (1): MedNeXtBlock(
+      (conv1): Conv3d(64, 64, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), groups=64)
+      (norm): GroupNorm(64, 64, eps=1e-05, affine=True)
+      (conv2): Conv3d(64, 192, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+      (act): GELU(approximate='none')
+      (conv3): Conv3d(192, 64, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    )
+  )
+  (up_0): MedNeXtUpBlock(
+    (conv1): ConvTranspose3d(64, 64, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1), groups=64)
+    (norm): GroupNorm(64, 64, eps=1e-05, affine=True)
+    (conv2): Conv3d(64, 128, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    (act): GELU(approximate='none')
+    (conv3): Conv3d(128, 32, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    (res_conv): ConvTranspose3d(64, 32, kernel_size=(1, 1, 1), stride=(2, 2, 2))
+  )
+  (dec_block_0): Sequential(
+    (0): MedNeXtBlock(
+      (conv1): Conv3d(32, 32, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), groups=32)
+      (norm): GroupNorm(32, 32, eps=1e-05, affine=True)
+      (conv2): Conv3d(32, 64, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+      (act): GELU(approximate='none')
+      (conv3): Conv3d(64, 32, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    )
+    (1): MedNeXtBlock(
+      (conv1): Conv3d(32, 32, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), groups=32)
+      (norm): GroupNorm(32, 32, eps=1e-05, affine=True)
+      (conv2): Conv3d(32, 64, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+      (act): GELU(approximate='none')
+      (conv3): Conv3d(64, 32, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+    )
+  )
+  (out_0): OutBlock(
+    (conv_out): ConvTranspose3d(32, 37, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+  )
+  (out_1): OutBlock(
+    (conv_out): ConvTranspose3d(64, 37, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+  )
+  (out_2): OutBlock(
+    (conv_out): ConvTranspose3d(128, 37, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+  )
+  (out_3): OutBlock(
+    (conv_out): ConvTranspose3d(256, 37, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+  )
+  (out_4): OutBlock(
+    (conv_out): ConvTranspose3d(512, 37, kernel_size=(1, 1, 1), stride=(1, 1, 1))
+  )
+) 
+2026-10-18 20:06:57.170567: 
+ 
+2026-10-18 20:06:57.173394: 
+epoch:  150 
+2026-10-18 20:11:16.905052: train loss : -0.7522 
+2026-10-18 20:11:22.298997: validation loss: -0.6835 
+2026-10-18 20:11:22.300260: Average global foreground Dice: [np.float32(0.9439), np.float32(0.7164), np.float32(0.8784), np.float32(0.8845), np.float32(0.8235), np.float32(0.9373), np.float32(0.8539), np.float32(0.1389), np.float32(0.0), np.float32(0.0), np.float32(0.7587), np.float32(0.8073), np.float32(0.6958), np.float32(0.5599), np.float32(0.0), np.float32(0.0), np.float32(0.7949), np.float32(0.6025), np.float32(0.7957), np.float32(0.6631), np.float32(0.3505), np.float32(0.7095), np.float32(0.9338), np.float32(0.9229), np.float32(0.6672), np.float32(0.658), np.float32(0.4266), np.float32(0.8423), np.float32(0.5616), np.float32(0.7409), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9594), np.float32(0.9693)] 
+2026-10-18 20:11:22.300519: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 20:11:22.684292: lr: 0.000863 
+2026-10-18 20:11:22.684550: This epoch took 265.510808 s
+ 
+2026-10-18 20:11:22.684634: 
+epoch:  151 
+2026-10-18 20:15:15.538577: train loss : -0.7513 
+2026-10-18 20:15:20.882137: validation loss: -0.6647 
+2026-10-18 20:15:20.882953: Average global foreground Dice: [np.float32(0.9103), np.float32(0.6979), np.float32(0.8534), np.float32(0.857), np.float32(0.7966), np.float32(0.9246), np.float32(0.8831), np.float32(0.1367), np.float32(0.0), np.float32(0.0), np.float32(0.7453), np.float32(0.7667), np.float32(0.6517), np.float32(0.3534), np.float32(0.0), np.float32(0.0), np.float32(0.821), np.float32(0.6674), np.float32(0.85), np.float32(0.7232), np.float32(0.2661), np.float32(0.7696), np.float32(0.9303), np.float32(0.9166), np.float32(0.6126), np.float32(0.6624), np.float32(0.1866), np.float32(0.4453), np.float32(0.5545), np.float32(0.7333), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9569), np.float32(0.9696)] 
+2026-10-18 20:15:20.883246: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 20:15:21.210641: lr: 0.000862 
+2026-10-18 20:15:21.211001: This epoch took 238.526115 s
+ 
+2026-10-18 20:15:21.211120: 
+epoch:  152 
+2026-10-18 20:19:26.884002: train loss : -0.7600 
+2026-10-18 20:19:32.236383: validation loss: -0.6853 
+2026-10-18 20:19:32.237251: Average global foreground Dice: [np.float32(0.9398), np.float32(0.7029), np.float32(0.847), np.float32(0.8742), np.float32(0.8053), np.float32(0.9312), np.float32(0.8618), np.float32(0.7477), np.float32(0.0), np.float32(0.3433), np.float32(0.7835), np.float32(0.8099), np.float32(0.6899), np.float32(0.5497), np.float32(0.0), np.float32(0.0), np.float32(0.8215), np.float32(0.6567), np.float32(0.8299), np.float32(0.7182), np.float32(0.2861), np.float32(0.6276), np.float32(0.9324), np.float32(0.9204), np.float32(0.6233), np.float32(0.6756), np.float32(0.4105), np.float32(0.8692), np.float32(0.5782), np.float32(0.621), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9584), np.float32(0.969)] 
+2026-10-18 20:19:32.237415: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 20:19:32.583795: lr: 0.000861 
+2026-10-18 20:19:32.584145: This epoch took 251.372946 s
+ 
+2026-10-18 20:19:32.584362: 
+epoch:  153 
+2026-10-18 20:23:47.094445: train loss : -0.7561 
+2026-10-18 20:23:52.442883: validation loss: -0.6989 
+2026-10-18 20:23:52.443878: Average global foreground Dice: [np.float32(0.9306), np.float32(0.6985), np.float32(0.8708), np.float32(0.8749), np.float32(0.8251), np.float32(0.9386), np.float32(0.8876), np.float32(0.7586), np.float32(0.0), np.float32(0.45), np.float32(0.7504), np.float32(0.8385), np.float32(0.7319), np.float32(0.577), np.float32(0.0), np.float32(0.0), np.float32(0.8348), np.float32(0.6681), np.float32(0.8453), np.float32(0.715), np.float32(0.3131), np.float32(0.7263), np.float32(0.908), np.float32(0.9108), np.float32(0.6705), np.float32(0.7138), np.float32(0.4213), np.float32(0.8939), np.float32(0.6064), np.float32(0.7616), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9522), np.float32(0.9674)] 
+2026-10-18 20:23:52.444044: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 20:23:52.780919: lr: 0.00086 
+2026-10-18 20:23:52.781156: This epoch took 260.196713 s
+ 
+2026-10-18 20:23:52.781239: 
+epoch:  154 
+2026-10-18 20:28:14.230878: train loss : -0.7599 
+2026-10-18 20:28:19.608569: validation loss: -0.7133 
+2026-10-18 20:28:19.609629: Average global foreground Dice: [np.float32(0.9411), np.float32(0.7744), np.float32(0.8882), np.float32(0.8916), np.float32(0.8284), np.float32(0.9252), np.float32(0.8895), np.float32(0.8457), np.float32(0.0), np.float32(0.6112), np.float32(0.7631), np.float32(0.8137), np.float32(0.7155), np.float32(0.5936), np.float32(0.0), np.float32(0.0), np.float32(0.8331), np.float32(0.6562), np.float32(0.8462), np.float32(0.7237), np.float32(0.4795), np.float32(0.7748), np.float32(0.9305), np.float32(0.9141), np.float32(0.6794), np.float32(0.6872), np.float32(0.4446), np.float32(0.8652), np.float32(0.6918), np.float32(0.7819), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9618), np.float32(0.9676)] 
+2026-10-18 20:28:19.609921: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 20:28:19.914819: lr: 0.000859 
+2026-10-18 20:28:19.915221: This epoch took 267.133919 s
+ 
+2026-10-18 20:28:19.915513: 
+epoch:  155 
+2026-10-18 20:32:37.496644: train loss : -0.7522 
+2026-10-18 20:32:42.846344: validation loss: -0.7050 
+2026-10-18 20:32:42.847532: Average global foreground Dice: [np.float32(0.9396), np.float32(0.7109), np.float32(0.864), np.float32(0.8922), np.float32(0.8261), np.float32(0.9273), np.float32(0.8912), np.float32(0.7942), np.float32(0.0), np.float32(0.6167), np.float32(0.783), np.float32(0.8285), np.float32(0.6979), np.float32(0.5518), np.float32(0.062), np.float32(0.0), np.float32(0.8392), np.float32(0.64), np.float32(0.8404), np.float32(0.7038), np.float32(0.3778), np.float32(0.7463), np.float32(0.8809), np.float32(0.8841), np.float32(0.661), np.float32(0.6376), np.float32(0.3636), np.float32(0.8862), np.float32(0.6405), np.float32(0.8089), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9544), np.float32(0.9667)] 
+2026-10-18 20:32:42.848000: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 20:32:43.207462: lr: 0.000858 
+2026-10-18 20:32:43.207818: This epoch took 263.292080 s
+ 
+2026-10-18 20:32:43.208113: 
+epoch:  156 
+2026-10-18 20:37:26.205360: train loss : -0.7566 
+2026-10-18 20:37:31.576367: validation loss: -0.6994 
+2026-10-18 20:37:31.577543: Average global foreground Dice: [np.float32(0.9277), np.float32(0.7402), np.float32(0.8731), np.float32(0.887), np.float32(0.7953), np.float32(0.9054), np.float32(0.8904), np.float32(0.6512), np.float32(0.0), np.float32(0.5769), np.float32(0.7842), np.float32(0.8287), np.float32(0.6845), np.float32(0.5845), np.float32(0.0), np.float32(0.0), np.float32(0.8236), np.float32(0.6711), np.float32(0.8441), np.float32(0.7333), np.float32(0.3227), np.float32(0.793), np.float32(0.9236), np.float32(0.917), np.float32(0.674), np.float32(0.6919), np.float32(0.4478), np.float32(0.8566), np.float32(0.6487), np.float32(0.7392), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.959), np.float32(0.968)] 
+2026-10-18 20:37:31.577838: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 20:37:31.881654: lr: 0.000858 
+2026-10-18 20:37:31.881918: This epoch took 288.673677 s
+ 
+2026-10-18 20:37:31.882007: 
+epoch:  157 
+2026-10-18 20:42:02.102985: train loss : -0.7562 
+2026-10-18 20:42:07.461259: validation loss: -0.6941 
+2026-10-18 20:42:07.462175: Average global foreground Dice: [np.float32(0.9448), np.float32(0.7604), np.float32(0.8747), np.float32(0.8976), np.float32(0.7821), np.float32(0.9324), np.float32(0.8797), np.float32(0.6859), np.float32(0.0), np.float32(0.5491), np.float32(0.7906), np.float32(0.8206), np.float32(0.7089), np.float32(0.6326), np.float32(0.0), np.float32(0.0), np.float32(0.8288), np.float32(0.6776), np.float32(0.8427), np.float32(0.7441), np.float32(0.3503), np.float32(0.7398), np.float32(0.9094), np.float32(0.9068), np.float32(0.681), np.float32(0.6968), np.float32(0.4295), np.float32(0.8523), np.float32(0.5972), np.float32(0.7159), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9621), np.float32(0.9696)] 
+2026-10-18 20:42:07.462469: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 20:42:07.790166: lr: 0.000857 
+2026-10-18 20:42:07.790416: This epoch took 275.908231 s
+ 
+2026-10-18 20:42:07.790503: 
+epoch:  158 
+2026-10-18 20:46:36.340936: train loss : -0.7635 
+2026-10-18 20:46:41.721008: validation loss: -0.6904 
+2026-10-18 20:46:41.721981: Average global foreground Dice: [np.float32(0.9133), np.float32(0.7311), np.float32(0.8788), np.float32(0.8902), np.float32(0.8213), np.float32(0.9385), np.float32(0.8828), np.float32(0.8036), np.float32(0.0), np.float32(0.5371), np.float32(0.7782), np.float32(0.8287), np.float32(0.6601), np.float32(0.6101), np.float32(0.0), np.float32(0.0), np.float32(0.8373), np.float32(0.703), np.float32(0.8469), np.float32(0.7568), np.float32(0.3011), np.float32(0.774), np.float32(0.9021), np.float32(0.8734), np.float32(0.7049), np.float32(0.6952), np.float32(0.4265), np.float32(0.8779), np.float32(0.4236), np.float32(0.6156), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9604), np.float32(0.968)] 
+2026-10-18 20:46:41.722143: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 20:46:42.011686: lr: 0.000856 
+2026-10-18 20:46:42.029931: saving checkpoint... 
+2026-10-18 20:46:42.162857: done, saving took 0.15 seconds 
+2026-10-18 20:46:42.164588: This epoch took 274.374016 s
+ 
+2026-10-18 20:46:42.164802: 
+epoch:  159 
+2026-10-18 20:50:36.751414: train loss : -0.7684 
+2026-10-18 20:50:42.097901: validation loss: -0.6957 
+2026-10-18 20:50:42.098825: Average global foreground Dice: [np.float32(0.9449), np.float32(0.6933), np.float32(0.8636), np.float32(0.8818), np.float32(0.8109), np.float32(0.9413), np.float32(0.8916), np.float32(0.7445), np.float32(0.0), np.float32(0.1667), np.float32(0.7699), np.float32(0.8218), np.float32(0.6931), np.float32(0.5991), np.float32(0.0), np.float32(0.0), np.float32(0.8151), np.float32(0.6259), np.float32(0.8357), np.float32(0.7018), np.float32(0.2465), np.float32(0.7594), np.float32(0.9269), np.float32(0.9062), np.float32(0.6215), np.float32(0.6742), np.float32(0.3817), np.float32(0.8841), np.float32(0.577), np.float32(0.7583), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.954), np.float32(0.9682)] 
+2026-10-18 20:50:42.098972: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 20:50:42.406802: lr: 0.000855 
+2026-10-18 20:50:42.456977: saving checkpoint... 
+2026-10-18 20:50:42.594905: done, saving took 0.19 seconds 
+2026-10-18 20:50:42.596451: This epoch took 240.431550 s
+ 
+2026-10-18 20:50:42.596637: 
+epoch:  160 
+2026-10-18 20:55:05.335263: train loss : -0.7610 
+2026-10-18 20:55:10.701212: validation loss: -0.6944 
+2026-10-18 20:55:10.702192: Average global foreground Dice: [np.float32(0.9386), np.float32(0.7233), np.float32(0.861), np.float32(0.8878), np.float32(0.8287), np.float32(0.9387), np.float32(0.8938), np.float32(0.759), np.float32(0.0), np.float32(0.2771), np.float32(0.7916), np.float32(0.8257), np.float32(0.6789), np.float32(0.6475), np.float32(0.0), np.float32(0.0), np.float32(0.8351), np.float32(0.6832), np.float32(0.8412), np.float32(0.7136), np.float32(0.2536), np.float32(0.7358), np.float32(0.9331), np.float32(0.9121), np.float32(0.647), np.float32(0.6483), np.float32(0.4227), np.float32(0.866), np.float32(0.6529), np.float32(0.7624), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9555), np.float32(0.9685)] 
+2026-10-18 20:55:10.702513: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 20:55:10.995352: lr: 0.000854 
+2026-10-18 20:55:11.050987: saving checkpoint... 
+2026-10-18 20:55:11.183008: done, saving took 0.19 seconds 
+2026-10-18 20:55:11.184550: This epoch took 268.587816 s
+ 
+2026-10-18 20:55:11.184652: 
+epoch:  161 
+2026-10-18 20:59:39.479596: train loss : -0.7676 
+2026-10-18 20:59:44.830726: validation loss: -0.6966 
+2026-10-18 20:59:44.831792: Average global foreground Dice: [np.float32(0.9462), np.float32(0.7098), np.float32(0.8601), np.float32(0.8907), np.float32(0.8075), np.float32(0.9335), np.float32(0.8956), np.float32(0.7924), np.float32(0.0), np.float32(0.612), np.float32(0.783), np.float32(0.8438), np.float32(0.7006), np.float32(0.6084), np.float32(0.135), np.float32(0.0), np.float32(0.8207), np.float32(0.634), np.float32(0.8421), np.float32(0.6993), np.float32(0.3318), np.float32(0.7509), np.float32(0.9369), np.float32(0.917), np.float32(0.6599), np.float32(0.6584), np.float32(0.4432), np.float32(0.8425), np.float32(0.6373), np.float32(0.7002), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9536), np.float32(0.9692)] 
+2026-10-18 20:59:44.832100: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 20:59:45.142276: lr: 0.000853 
+2026-10-18 20:59:45.183831: saving checkpoint... 
+2026-10-18 20:59:45.323946: done, saving took 0.18 seconds 
+2026-10-18 20:59:45.325184: This epoch took 274.140397 s
+ 
+2026-10-18 20:59:45.325317: 
+epoch:  162 
+2026-10-18 21:04:11.614669: train loss : -0.7684 
+2026-10-18 21:04:16.993571: validation loss: -0.6943 
+2026-10-18 21:04:16.994601: Average global foreground Dice: [np.float32(0.9061), np.float32(0.6857), np.float32(0.8572), np.float32(0.8559), np.float32(0.7727), np.float32(0.9355), np.float32(0.8938), np.float32(0.29), np.float32(0.0), np.float32(0.6167), np.float32(0.7578), np.float32(0.8187), np.float32(0.734), np.float32(0.6209), np.float32(0.0098), np.float32(0.0), np.float32(0.824), np.float32(0.6249), np.float32(0.8378), np.float32(0.6268), np.float32(0.2946), np.float32(0.7011), np.float32(0.9002), np.float32(0.8852), np.float32(0.6087), np.float32(0.6563), np.float32(0.2781), np.float32(0.841), np.float32(0.5948), np.float32(0.7204), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.961), np.float32(0.9662)] 
+2026-10-18 21:04:16.994940: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 21:04:17.339069: lr: 0.000852 
+2026-10-18 21:04:17.339236: This epoch took 272.013839 s
+ 
+2026-10-18 21:04:17.339505: 
+epoch:  163 
+2026-10-18 21:08:20.564862: train loss : -0.7627 
+2026-10-18 21:08:25.913999: validation loss: -0.6854 
+2026-10-18 21:08:25.915170: Average global foreground Dice: [np.float32(0.9432), np.float32(0.7053), np.float32(0.868), np.float32(0.899), np.float32(0.8), np.float32(0.9137), np.float32(0.8761), np.float32(0.4585), np.float32(0.0), np.float32(0.6305), np.float32(0.7907), np.float32(0.8044), np.float32(0.6828), np.float32(0.5001), np.float32(0.0), np.float32(0.0), np.float32(0.8227), np.float32(0.6614), np.float32(0.8468), np.float32(0.7142), np.float32(0.3008), np.float32(0.7848), np.float32(0.9282), np.float32(0.9054), np.float32(0.6403), np.float32(0.6924), np.float32(0.4268), np.float32(0.8001), np.float32(0.6187), np.float32(0.7587), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9513), np.float32(0.9621)] 
+2026-10-18 21:08:25.915438: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 21:08:26.234909: lr: 0.000851 
+2026-10-18 21:08:26.235300: This epoch took 248.895570 s
+ 
+2026-10-18 21:08:26.235574: 
+epoch:  164 
+2026-10-18 21:12:49.356262: train loss : -0.7650 
+2026-10-18 21:12:54.701642: validation loss: -0.6980 
+2026-10-18 21:12:54.702878: Average global foreground Dice: [np.float32(0.935), np.float32(0.7161), np.float32(0.8693), np.float32(0.8757), np.float32(0.8024), np.float32(0.9322), np.float32(0.8908), np.float32(0.7747), np.float32(0.0), np.float32(0.5204), np.float32(0.7922), np.float32(0.815), np.float32(0.6941), np.float32(0.5873), np.float32(0.0092), np.float32(0.0), np.float32(0.8346), np.float32(0.6677), np.float32(0.8392), np.float32(0.7247), np.float32(0.3159), np.float32(0.7764), np.float32(0.9203), np.float32(0.9017), np.float32(0.6499), np.float32(0.7), np.float32(0.4084), np.float32(0.8361), np.float32(0.5583), np.float32(0.7693), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9605), np.float32(0.9698)] 
+2026-10-18 21:12:54.703372: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 21:12:54.989502: lr: 0.00085 
+2026-10-18 21:12:54.997591: saving checkpoint... 
+2026-10-18 21:12:55.141772: done, saving took 0.15 seconds 
+2026-10-18 21:12:55.143192: This epoch took 268.907514 s
+ 
+2026-10-18 21:12:55.143418: 
+epoch:  165 
+2026-10-18 21:17:08.310455: train loss : -0.7667 
+2026-10-18 21:17:13.654126: validation loss: -0.7009 
+2026-10-18 21:17:13.655015: Average global foreground Dice: [np.float32(0.9442), np.float32(0.7524), np.float32(0.8579), np.float32(0.8821), np.float32(0.8115), np.float32(0.9364), np.float32(0.8974), np.float32(0.8138), np.float32(0.0), np.float32(0.4736), np.float32(0.7824), np.float32(0.8082), np.float32(0.6919), np.float32(0.6359), np.float32(0.0097), np.float32(0.0), np.float32(0.8349), np.float32(0.6627), np.float32(0.8446), np.float32(0.7165), np.float32(0.3912), np.float32(0.7864), np.float32(0.9263), np.float32(0.9173), np.float32(0.6906), np.float32(0.6852), np.float32(0.3488), np.float32(0.8526), np.float32(0.6224), np.float32(0.7726), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9572), np.float32(0.9689)] 
+2026-10-18 21:17:13.655411: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 21:17:13.953413: lr: 0.000849 
+2026-10-18 21:17:13.962163: saving checkpoint... 
+2026-10-18 21:17:14.092411: done, saving took 0.14 seconds 
+2026-10-18 21:17:14.094001: This epoch took 258.950401 s
+ 
+2026-10-18 21:17:14.094195: 
+epoch:  166 
+2026-10-18 21:21:47.490746: train loss : -0.7614 
+2026-10-18 21:21:52.845042: validation loss: -0.6940 
+2026-10-18 21:21:52.846055: Average global foreground Dice: [np.float32(0.9446), np.float32(0.7045), np.float32(0.8574), np.float32(0.8801), np.float32(0.7698), np.float32(0.9334), np.float32(0.8818), np.float32(0.7481), np.float32(0.0), np.float32(0.5831), np.float32(0.7723), np.float32(0.8345), np.float32(0.6884), np.float32(0.5699), np.float32(0.0), np.float32(0.0), np.float32(0.8226), np.float32(0.6708), np.float32(0.8425), np.float32(0.718), np.float32(0.3412), np.float32(0.7902), np.float32(0.9124), np.float32(0.9027), np.float32(0.651), np.float32(0.6927), np.float32(0.4211), np.float32(0.8284), np.float32(0.6273), np.float32(0.7089), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9542), np.float32(0.964)] 
+2026-10-18 21:21:52.846463: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 21:21:53.133165: lr: 0.000848 
+2026-10-18 21:21:53.142351: saving checkpoint... 
+2026-10-18 21:21:53.273374: done, saving took 0.14 seconds 
+2026-10-18 21:21:53.275154: This epoch took 279.180871 s
+ 
+2026-10-18 21:21:53.275425: 
+epoch:  167 
+2026-10-18 21:26:59.732291: train loss : -0.7699 
+2026-10-18 21:27:05.103398: validation loss: -0.7000 
+2026-10-18 21:27:05.104362: Average global foreground Dice: [np.float32(0.9407), np.float32(0.7398), np.float32(0.8626), np.float32(0.8647), np.float32(0.7795), np.float32(0.9277), np.float32(0.8912), np.float32(0.4164), np.float32(0.0), np.float32(0.5946), np.float32(0.8001), np.float32(0.8337), np.float32(0.7133), np.float32(0.6508), np.float32(0.0), np.float32(0.0), np.float32(0.8208), np.float32(0.6482), np.float32(0.8415), np.float32(0.7461), np.float32(0.3521), np.float32(0.8145), np.float32(0.9266), np.float32(0.912), np.float32(0.6541), np.float32(0.6669), np.float32(0.4325), np.float32(0.818), np.float32(0.6265), np.float32(0.7162), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9572), np.float32(0.968)] 
+2026-10-18 21:27:05.104697: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 21:27:05.401311: lr: 0.000847 
+2026-10-18 21:27:05.410270: saving checkpoint... 
+2026-10-18 21:27:05.546915: done, saving took 0.15 seconds 
+2026-10-18 21:27:05.548497: This epoch took 312.272965 s
+ 
+2026-10-18 21:27:05.548671: 
+epoch:  168 
+2026-10-18 21:31:51.857339: train loss : -0.7637 
+2026-10-18 21:31:57.199158: validation loss: -0.6970 
+2026-10-18 21:31:57.200315: Average global foreground Dice: [np.float32(0.9384), np.float32(0.6948), np.float32(0.8654), np.float32(0.8967), np.float32(0.7868), np.float32(0.9251), np.float32(0.8812), np.float32(0.7337), np.float32(0.0), np.float32(0.5331), np.float32(0.776), np.float32(0.8254), np.float32(0.7106), np.float32(0.6715), np.float32(0.1219), np.float32(0.0), np.float32(0.8231), np.float32(0.6849), np.float32(0.8427), np.float32(0.718), np.float32(0.2729), np.float32(0.7534), np.float32(0.9163), np.float32(0.8887), np.float32(0.6356), np.float32(0.6532), np.float32(0.4036), np.float32(0.842), np.float32(0.6036), np.float32(0.7231), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9484), np.float32(0.9616)] 
+2026-10-18 21:31:57.200675: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 21:31:57.494575: lr: 0.000847 
+2026-10-18 21:31:57.502626: saving checkpoint... 
+2026-10-18 21:31:57.641386: done, saving took 0.15 seconds 
+2026-10-18 21:31:57.642802: This epoch took 292.094033 s
+ 
+2026-10-18 21:31:57.643020: 
+epoch:  169 
+2026-10-18 21:36:12.287838: train loss : -0.7589 
+2026-10-18 21:36:17.632522: validation loss: -0.6972 
+2026-10-18 21:36:17.633536: Average global foreground Dice: [np.float32(0.935), np.float32(0.7124), np.float32(0.8643), np.float32(0.8865), np.float32(0.8028), np.float32(0.9258), np.float32(0.8951), np.float32(0.6317), np.float32(0.0), np.float32(0.4369), np.float32(0.7798), np.float32(0.8435), np.float32(0.6808), np.float32(0.6048), np.float32(0.0), np.float32(0.0), np.float32(0.8188), np.float32(0.66), np.float32(0.8458), np.float32(0.7506), np.float32(0.2768), np.float32(0.7685), np.float32(0.9279), np.float32(0.9092), np.float32(0.7023), np.float32(0.5993), np.float32(0.3807), np.float32(0.5926), np.float32(0.5848), np.float32(0.7551), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9529), np.float32(0.9671)] 
+2026-10-18 21:36:17.634087: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 21:36:17.919577: lr: 0.000846 
+2026-10-18 21:36:17.919817: This epoch took 260.276698 s
+ 
+2026-10-18 21:36:17.919903: 
+epoch:  170 
+2026-10-18 21:40:35.628103: train loss : -0.7678 
+2026-10-18 21:40:41.002945: validation loss: -0.7048 
+2026-10-18 21:40:41.003941: Average global foreground Dice: [np.float32(0.9344), np.float32(0.6821), np.float32(0.8674), np.float32(0.8749), np.float32(0.778), np.float32(0.9265), np.float32(0.863), np.float32(0.8225), np.float32(0.0), np.float32(0.5118), np.float32(0.7842), np.float32(0.8525), np.float32(0.7353), np.float32(0.6403), np.float32(0.0828), np.float32(0.0), np.float32(0.8226), np.float32(0.6484), np.float32(0.8423), np.float32(0.7219), np.float32(0.28), np.float32(0.7468), np.float32(0.9237), np.float32(0.9014), np.float32(0.6329), np.float32(0.6842), np.float32(0.4584), np.float32(0.8355), np.float32(0.5859), np.float32(0.7522), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9496), np.float32(0.9675)] 
+2026-10-18 21:40:41.004124: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 21:40:41.294631: lr: 0.000845 
+2026-10-18 21:40:41.304644: saving checkpoint... 
+2026-10-18 21:40:41.432816: done, saving took 0.14 seconds 
+2026-10-18 21:40:41.434585: This epoch took 263.514626 s
+ 
+2026-10-18 21:40:41.434780: 
+epoch:  171 
+2026-10-18 21:44:38.427777: train loss : -0.7731 
+2026-10-18 21:44:43.776502: validation loss: -0.6956 
+2026-10-18 21:44:43.777484: Average global foreground Dice: [np.float32(0.9257), np.float32(0.6959), np.float32(0.8736), np.float32(0.903), np.float32(0.8078), np.float32(0.9291), np.float32(0.8832), np.float32(0.3964), np.float32(0.0), np.float32(0.5555), np.float32(0.7857), np.float32(0.8215), np.float32(0.7097), np.float32(0.5656), np.float32(0.0), np.float32(0.0), np.float32(0.8269), np.float32(0.6812), np.float32(0.8511), np.float32(0.7469), np.float32(0.4265), np.float32(0.7496), np.float32(0.9236), np.float32(0.9072), np.float32(0.5991), np.float32(0.678), np.float32(0.4349), np.float32(0.825), np.float32(0.62), np.float32(0.7391), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.953), np.float32(0.9674)] 
+2026-10-18 21:44:43.777946: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 21:44:44.069834: lr: 0.000844 
+2026-10-18 21:44:44.080200: saving checkpoint... 
+2026-10-18 21:44:44.213199: done, saving took 0.14 seconds 
+2026-10-18 21:44:44.214767: This epoch took 242.779896 s
+ 
+2026-10-18 21:44:44.214903: 
+epoch:  172 
+2026-10-18 21:48:58.021597: train loss : -0.7685 
+2026-10-18 21:49:03.386931: validation loss: -0.6943 
+2026-10-18 21:49:03.387835: Average global foreground Dice: [np.float32(0.9446), np.float32(0.7051), np.float32(0.875), np.float32(0.877), np.float32(0.7936), np.float32(0.9317), np.float32(0.8783), np.float32(0.8144), np.float32(0.0), np.float32(0.051), np.float32(0.777), np.float32(0.7799), np.float32(0.7242), np.float32(0.5993), np.float32(0.0), np.float32(0.0), np.float32(0.8323), np.float32(0.6574), np.float32(0.8403), np.float32(0.7043), np.float32(0.2434), np.float32(0.7714), np.float32(0.9356), np.float32(0.924), np.float32(0.6467), np.float32(0.6872), np.float32(0.3838), np.float32(0.8582), np.float32(0.6069), np.float32(0.7792), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9575), np.float32(0.9685)] 
+2026-10-18 21:49:03.387983: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 21:49:03.694255: lr: 0.000843 
+2026-10-18 21:49:03.694506: This epoch took 259.479420 s
+ 
+2026-10-18 21:49:03.694601: 
+epoch:  173 
+2026-10-18 21:53:14.036490: train loss : -0.7706 
+2026-10-18 21:53:19.382440: validation loss: -0.6990 
+2026-10-18 21:53:19.383316: Average global foreground Dice: [np.float32(0.9486), np.float32(0.7227), np.float32(0.8635), np.float32(0.8853), np.float32(0.8362), np.float32(0.9183), np.float32(0.8875), np.float32(0.743), np.float32(0.0), np.float32(0.535), np.float32(0.7689), np.float32(0.8056), np.float32(0.6978), np.float32(0.5944), np.float32(0.0106), np.float32(0.0), np.float32(0.8186), np.float32(0.6701), np.float32(0.8445), np.float32(0.7333), np.float32(0.3061), np.float32(0.7569), np.float32(0.9245), np.float32(0.9206), np.float32(0.6607), np.float32(0.6738), np.float32(0.2944), np.float32(0.8441), np.float32(0.6121), np.float32(0.7336), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9565), np.float32(0.9663)] 
+2026-10-18 21:53:19.383467: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 21:53:19.689477: lr: 0.000842 
+2026-10-18 21:53:19.697343: saving checkpoint... 
+2026-10-18 21:53:19.824674: done, saving took 0.13 seconds 
+2026-10-18 21:53:19.825936: This epoch took 256.131162 s
+ 
+2026-10-18 21:53:19.826120: 
+epoch:  174 
+2026-10-18 21:57:06.636540: train loss : -0.7744 
+2026-10-18 21:57:12.007213: validation loss: -0.7006 
+2026-10-18 21:57:12.008571: Average global foreground Dice: [np.float32(0.9415), np.float32(0.7648), np.float32(0.8746), np.float32(0.8821), np.float32(0.8118), np.float32(0.9319), np.float32(0.884), np.float32(0.8017), np.float32(0.0), np.float32(0.5228), np.float32(0.7644), np.float32(0.8207), np.float32(0.7033), np.float32(0.6126), np.float32(0.0), np.float32(0.0), np.float32(0.8168), np.float32(0.6473), np.float32(0.8372), np.float32(0.6729), np.float32(0.3401), np.float32(0.7895), np.float32(0.9247), np.float32(0.9229), np.float32(0.6768), np.float32(0.654), np.float32(0.5063), np.float32(0.8403), np.float32(0.6364), np.float32(0.7741), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9583), np.float32(0.9653)] 
+2026-10-18 21:57:12.008909: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 21:57:12.316591: lr: 0.000841 
+2026-10-18 21:57:12.352348: saving checkpoint... 
+2026-10-18 21:57:12.500846: done, saving took 0.18 seconds 
+2026-10-18 21:57:12.502419: This epoch took 232.676136 s
+ 
+2026-10-18 21:57:12.502602: 
+epoch:  175 
+2026-10-18 22:01:40.821263: train loss : -0.7670 
+2026-10-18 22:01:46.188633: validation loss: -0.7142 
+2026-10-18 22:01:46.190081: Average global foreground Dice: [np.float32(0.9432), np.float32(0.7679), np.float32(0.8548), np.float32(0.8853), np.float32(0.833), np.float32(0.9257), np.float32(0.8897), np.float32(0.7844), np.float32(0.0), np.float32(0.6243), np.float32(0.7518), np.float32(0.801), np.float32(0.74), np.float32(0.6313), np.float32(0.0), np.float32(0.0), np.float32(0.8276), np.float32(0.6397), np.float32(0.8398), np.float32(0.7109), np.float32(0.3438), np.float32(0.8017), np.float32(0.9265), np.float32(0.9168), np.float32(0.6706), np.float32(0.6544), np.float32(0.462), np.float32(0.8446), np.float32(0.6555), np.float32(0.7652), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9527), np.float32(0.9615)] 
+2026-10-18 22:01:46.190410: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 22:01:46.529334: lr: 0.00084 
+2026-10-18 22:01:46.542831: saving checkpoint... 
+2026-10-18 22:01:46.683745: done, saving took 0.15 seconds 
+2026-10-18 22:01:46.685109: This epoch took 274.182435 s
+ 
+2026-10-18 22:01:46.685292: 
+epoch:  176 
+2026-10-18 22:06:07.514688: train loss : -0.7703 
+2026-10-18 22:06:12.872731: validation loss: -0.6976 
+2026-10-18 22:06:12.873826: Average global foreground Dice: [np.float32(0.9412), np.float32(0.7143), np.float32(0.8631), np.float32(0.8908), np.float32(0.7942), np.float32(0.932), np.float32(0.8761), np.float32(0.7261), np.float32(0.0), np.float32(0.3766), np.float32(0.7929), np.float32(0.8124), np.float32(0.7078), np.float32(0.5885), np.float32(0.0), np.float32(0.0), np.float32(0.8152), np.float32(0.6361), np.float32(0.8403), np.float32(0.6983), np.float32(0.3284), np.float32(0.7741), np.float32(0.9047), np.float32(0.9205), np.float32(0.6262), np.float32(0.6878), np.float32(0.4448), np.float32(0.8198), np.float32(0.5875), np.float32(0.7683), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9546), np.float32(0.9686)] 
+2026-10-18 22:06:12.874079: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 22:06:13.171163: lr: 0.000839 
+2026-10-18 22:06:13.171518: This epoch took 266.485967 s
+ 
+2026-10-18 22:06:13.171630: 
+epoch:  177 
+2026-10-18 22:09:56.990597: train loss : -0.7766 
+2026-10-18 22:10:02.369553: validation loss: -0.7056 
+2026-10-18 22:10:02.370461: Average global foreground Dice: [np.float32(0.9447), np.float32(0.6926), np.float32(0.8675), np.float32(0.8788), np.float32(0.7999), np.float32(0.9327), np.float32(0.8793), np.float32(0.7831), np.float32(0.0), np.float32(0.4859), np.float32(0.778), np.float32(0.8283), np.float32(0.7386), np.float32(0.5998), np.float32(0.0), np.float32(0.0), np.float32(0.8232), np.float32(0.65), np.float32(0.8251), np.float32(0.7079), np.float32(0.3044), np.float32(0.7775), np.float32(0.9332), np.float32(0.9305), np.float32(0.6497), np.float32(0.6769), np.float32(0.3669), np.float32(0.8571), np.float32(0.5798), np.float32(0.7682), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.953), np.float32(0.9692)] 
+2026-10-18 22:10:02.370632: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 22:10:02.670239: lr: 0.000838 
+2026-10-18 22:10:02.709066: saving checkpoint... 
+2026-10-18 22:10:02.849129: done, saving took 0.18 seconds 
+2026-10-18 22:10:02.850428: This epoch took 229.678516 s
+ 
+2026-10-18 22:10:02.850666: 
+epoch:  178 
+2026-10-18 22:14:40.179640: train loss : -0.7702 
+2026-10-18 22:14:45.545196: validation loss: -0.6956 
+2026-10-18 22:14:45.546472: Average global foreground Dice: [np.float32(0.9389), np.float32(0.687), np.float32(0.8718), np.float32(0.8866), np.float32(0.8065), np.float32(0.9415), np.float32(0.8855), np.float32(0.6788), np.float32(0.0), np.float32(0.5852), np.float32(0.7805), np.float32(0.821), np.float32(0.6995), np.float32(0.5498), np.float32(0.0409), np.float32(0.0), np.float32(0.832), np.float32(0.6705), np.float32(0.8414), np.float32(0.6984), np.float32(0.3393), np.float32(0.7836), np.float32(0.9146), np.float32(0.8983), np.float32(0.6499), np.float32(0.7008), np.float32(0.3933), np.float32(0.7843), np.float32(0.6208), np.float32(0.7495), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9578), np.float32(0.9661)] 
+2026-10-18 22:14:45.546742: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 22:14:45.874958: lr: 0.000837 
+2026-10-18 22:14:45.884210: saving checkpoint... 
+2026-10-18 22:14:46.019670: done, saving took 0.14 seconds 
+2026-10-18 22:14:46.021202: This epoch took 283.170373 s
+ 
+2026-10-18 22:14:46.021420: 
+epoch:  179 
+2026-10-18 22:19:29.133763: train loss : -0.7684 
+2026-10-18 22:19:34.521081: validation loss: -0.7073 
+2026-10-18 22:19:34.522222: Average global foreground Dice: [np.float32(0.9379), np.float32(0.6944), np.float32(0.8756), np.float32(0.8735), np.float32(0.7958), np.float32(0.9339), np.float32(0.8828), np.float32(0.6658), np.float32(0.0), np.float32(0.6211), np.float32(0.7944), np.float32(0.8515), np.float32(0.7064), np.float32(0.5634), np.float32(0.0168), np.float32(0.0), np.float32(0.8283), np.float32(0.6776), np.float32(0.8388), np.float32(0.7037), np.float32(0.3031), np.float32(0.829), np.float32(0.9298), np.float32(0.9264), np.float32(0.6761), np.float32(0.6822), np.float32(0.3952), np.float32(0.7972), np.float32(0.5812), np.float32(0.783), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9546), np.float32(0.9685)] 
+2026-10-18 22:19:34.522634: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 22:19:34.826912: lr: 0.000836 
+2026-10-18 22:19:34.841326: saving checkpoint... 
+2026-10-18 22:19:35.005728: done, saving took 0.18 seconds 
+2026-10-18 22:19:35.007131: This epoch took 288.985616 s
+ 
+2026-10-18 22:19:35.007332: 
+epoch:  180 
+2026-10-18 22:23:22.584087: train loss : -0.7732 
+2026-10-18 22:23:27.946779: validation loss: -0.7090 
+2026-10-18 22:23:27.948401: Average global foreground Dice: [np.float32(0.9468), np.float32(0.7353), np.float32(0.8667), np.float32(0.8762), np.float32(0.8113), np.float32(0.9394), np.float32(0.8787), np.float32(0.8364), np.float32(0.0), np.float32(0.5675), np.float32(0.7901), np.float32(0.8449), np.float32(0.7063), np.float32(0.605), np.float32(0.0), np.float32(0.0), np.float32(0.8263), np.float32(0.6743), np.float32(0.8368), np.float32(0.7015), np.float32(0.2837), np.float32(0.7991), np.float32(0.9232), np.float32(0.9174), np.float32(0.6416), np.float32(0.6443), np.float32(0.4915), np.float32(0.8616), np.float32(0.6101), np.float32(0.731), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9596), np.float32(0.9692)] 
+2026-10-18 22:23:27.949540: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 22:23:28.286928: lr: 0.000836 
+2026-10-18 22:23:28.348560: saving checkpoint... 
+2026-10-18 22:23:29.462734: done, saving took 1.18 seconds 
+2026-10-18 22:23:29.464183: This epoch took 234.456723 s
+ 
+2026-10-18 22:23:29.464370: 
+epoch:  181 
+2026-10-18 22:27:43.630055: train loss : -0.7729 
+2026-10-18 22:27:49.000684: validation loss: -0.6760 
+2026-10-18 22:27:49.001674: Average global foreground Dice: [np.float32(0.9446), np.float32(0.6964), np.float32(0.8656), np.float32(0.8702), np.float32(0.8059), np.float32(0.926), np.float32(0.8795), np.float32(0.8136), np.float32(0.0), np.float32(0.5584), np.float32(0.7521), np.float32(0.7875), np.float32(0.6692), np.float32(0.5292), np.float32(0.0249), np.float32(0.0), np.float32(0.8251), np.float32(0.6662), np.float32(0.8347), np.float32(0.7137), np.float32(0.4105), np.float32(0.7782), np.float32(0.9078), np.float32(0.8971), np.float32(0.6423), np.float32(0.6975), np.float32(0.4162), np.float32(0.8554), np.float32(0.5525), np.float32(0.7522), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9516), np.float32(0.9648)] 
+2026-10-18 22:27:49.002244: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 22:27:49.304308: lr: 0.000835 
+2026-10-18 22:27:49.394709: saving checkpoint... 
+2026-10-18 22:27:49.539424: done, saving took 0.23 seconds 
+2026-10-18 22:27:49.540951: This epoch took 260.076499 s
+ 
+2026-10-18 22:27:49.541120: 
+epoch:  182 
+2026-10-18 22:32:06.402021: train loss : -0.7669 
+2026-10-18 22:32:11.746056: validation loss: -0.7104 
+2026-10-18 22:32:11.747114: Average global foreground Dice: [np.float32(0.9253), np.float32(0.7505), np.float32(0.8538), np.float32(0.8764), np.float32(0.8122), np.float32(0.9328), np.float32(0.8846), np.float32(0.7298), np.float32(0.0), np.float32(0.5695), np.float32(0.7842), np.float32(0.8298), np.float32(0.7141), np.float32(0.6255), np.float32(0.0), np.float32(0.0), np.float32(0.824), np.float32(0.6479), np.float32(0.8312), np.float32(0.6897), np.float32(0.3428), np.float32(0.8065), np.float32(0.9228), np.float32(0.9125), np.float32(0.6658), np.float32(0.6571), np.float32(0.2908), np.float32(0.8464), np.float32(0.5768), np.float32(0.7258), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9532), np.float32(0.966)] 
+2026-10-18 22:32:11.747809: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 22:32:12.039152: lr: 0.000834 
+2026-10-18 22:32:12.060478: saving checkpoint... 
+2026-10-18 22:32:12.191296: done, saving took 0.15 seconds 
+2026-10-18 22:32:12.192576: This epoch took 262.651368 s
+ 
+2026-10-18 22:32:12.192752: 
+epoch:  183 
+2026-10-18 22:36:03.140419: train loss : -0.7705 
+2026-10-18 22:36:08.504632: validation loss: -0.7030 
+2026-10-18 22:36:08.505929: Average global foreground Dice: [np.float32(0.9369), np.float32(0.7308), np.float32(0.8704), np.float32(0.8804), np.float32(0.8126), np.float32(0.9327), np.float32(0.8786), np.float32(0.6714), np.float32(0.0), np.float32(0.5509), np.float32(0.755), np.float32(0.8023), np.float32(0.71), np.float32(0.5947), np.float32(0.0), np.float32(0.0), np.float32(0.8174), np.float32(0.6644), np.float32(0.8326), np.float32(0.6859), np.float32(0.3121), np.float32(0.724), np.float32(0.9371), np.float32(0.928), np.float32(0.6368), np.float32(0.6769), np.float32(0.4179), np.float32(0.8531), np.float32(0.6275), np.float32(0.7402), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9565), np.float32(0.9691)] 
+2026-10-18 22:36:08.506239: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 22:36:08.853235: lr: 0.000833 
+2026-10-18 22:36:08.853497: This epoch took 236.660612 s
+ 
+2026-10-18 22:36:08.853596: 
+epoch:  184 
+2026-10-18 22:40:29.083332: train loss : -0.7767 
+2026-10-18 22:40:34.493782: validation loss: -0.6823 
+2026-10-18 22:40:34.495153: Average global foreground Dice: [np.float32(0.9442), np.float32(0.6941), np.float32(0.8696), np.float32(0.8844), np.float32(0.5567), np.float32(0.9257), np.float32(0.8785), np.float32(0.4276), np.float32(0.0), np.float32(0.5966), np.float32(0.7791), np.float32(0.796), np.float32(0.7126), np.float32(0.5528), np.float32(0.0), np.float32(0.0), np.float32(0.8059), np.float32(0.6778), np.float32(0.8411), np.float32(0.7457), np.float32(0.3843), np.float32(0.7648), np.float32(0.933), np.float32(0.9293), np.float32(0.6499), np.float32(0.6959), np.float32(0.4292), np.float32(0.8574), np.float32(0.6477), np.float32(0.7959), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.957), np.float32(0.9682)] 
+2026-10-18 22:40:34.495650: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 22:40:34.821070: lr: 0.000832 
+2026-10-18 22:40:34.821479: This epoch took 265.967827 s
+ 
+2026-10-18 22:40:34.821715: 
+epoch:  185 
+2026-10-18 22:44:59.828125: train loss : -0.7799 
+2026-10-18 22:45:05.185242: validation loss: -0.6767 
+2026-10-18 22:45:05.186337: Average global foreground Dice: [np.float32(0.9318), np.float32(0.6796), np.float32(0.8621), np.float32(0.8661), np.float32(0.8078), np.float32(0.9127), np.float32(0.8955), np.float32(0.4972), np.float32(0.0), np.float32(0.5048), np.float32(0.76), np.float32(0.8052), np.float32(0.7039), np.float32(0.5905), np.float32(0.0016), np.float32(0.0), np.float32(0.8082), np.float32(0.6031), np.float32(0.842), np.float32(0.7043), np.float32(0.2567), np.float32(0.7705), np.float32(0.913), np.float32(0.8997), np.float32(0.6099), np.float32(0.6551), np.float32(0.3764), np.float32(0.5503), np.float32(0.6248), np.float32(0.7221), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9412), np.float32(0.9611)] 
+2026-10-18 22:45:05.186631: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 22:45:05.480119: lr: 0.000831 
+2026-10-18 22:45:05.480587: This epoch took 270.658764 s
+ 
+2026-10-18 22:45:05.480876: 
+epoch:  186 
+2026-10-18 22:49:15.892767: train loss : -0.7751 
+2026-10-18 22:49:21.233922: validation loss: -0.6962 
+2026-10-18 22:49:21.235089: Average global foreground Dice: [np.float32(0.9386), np.float32(0.7292), np.float32(0.8698), np.float32(0.8553), np.float32(0.8126), np.float32(0.9327), np.float32(0.8763), np.float32(0.6861), np.float32(0.0), np.float32(0.5706), np.float32(0.795), np.float32(0.8313), np.float32(0.6915), np.float32(0.6209), np.float32(0.0), np.float32(0.0), np.float32(0.8301), np.float32(0.6629), np.float32(0.8401), np.float32(0.6926), np.float32(0.3323), np.float32(0.7549), np.float32(0.9317), np.float32(0.9251), np.float32(0.6888), np.float32(0.6655), np.float32(0.4603), np.float32(0.819), np.float32(0.6435), np.float32(0.788), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.949), np.float32(0.9682)] 
+2026-10-18 22:49:21.235486: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 22:49:21.546474: lr: 0.00083 
+2026-10-18 22:49:21.546940: This epoch took 256.065834 s
+ 
+2026-10-18 22:49:21.547240: 
+epoch:  187 
+2026-10-18 22:54:02.264231: train loss : -0.7617 
+2026-10-18 22:54:07.638724: validation loss: -0.7009 
+2026-10-18 22:54:07.640066: Average global foreground Dice: [np.float32(0.9417), np.float32(0.6943), np.float32(0.8607), np.float32(0.8777), np.float32(0.8241), np.float32(0.9238), np.float32(0.8707), np.float32(0.3243), np.float32(0.0), np.float32(0.5764), np.float32(0.7685), np.float32(0.81), np.float32(0.7241), np.float32(0.6362), np.float32(0.0046), np.float32(0.0), np.float32(0.8362), np.float32(0.6797), np.float32(0.8319), np.float32(0.7028), np.float32(0.3047), np.float32(0.7906), np.float32(0.9303), np.float32(0.9144), np.float32(0.6111), np.float32(0.6723), np.float32(0.462), np.float32(0.6925), np.float32(0.6072), np.float32(0.6346), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9551), np.float32(0.9675)] 
+2026-10-18 22:54:07.640434: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 22:54:07.930090: lr: 0.000829 
+2026-10-18 22:54:07.930354: This epoch took 286.382890 s
+ 
+2026-10-18 22:54:07.930451: 
+epoch:  188 
+2026-10-18 22:58:31.149282: train loss : -0.7671 
+2026-10-18 22:58:36.489486: validation loss: -0.7005 
+2026-10-18 22:58:36.490575: Average global foreground Dice: [np.float32(0.94), np.float32(0.74), np.float32(0.8564), np.float32(0.8932), np.float32(0.8042), np.float32(0.9351), np.float32(0.881), np.float32(0.7115), np.float32(0.0), np.float32(0.5351), np.float32(0.7869), np.float32(0.8208), np.float32(0.7209), np.float32(0.6629), np.float32(0.0), np.float32(0.0), np.float32(0.8035), np.float32(0.5858), np.float32(0.8103), np.float32(0.6747), np.float32(0.3215), np.float32(0.7758), np.float32(0.9246), np.float32(0.9186), np.float32(0.6382), np.float32(0.6203), np.float32(0.391), np.float32(0.7618), np.float32(0.6075), np.float32(0.6307), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9559), np.float32(0.9684)] 
+2026-10-18 22:58:36.491151: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 22:58:36.794697: lr: 0.000828 
+2026-10-18 22:58:36.794973: This epoch took 268.864456 s
+ 
+2026-10-18 22:58:36.795314: 
+epoch:  189 
+2026-10-18 23:03:10.800900: train loss : -0.7688 
+2026-10-18 23:03:16.174718: validation loss: -0.7036 
+2026-10-18 23:03:16.175805: Average global foreground Dice: [np.float32(0.9474), np.float32(0.7332), np.float32(0.86), np.float32(0.8659), np.float32(0.8174), np.float32(0.93), np.float32(0.8842), np.float32(0.8284), np.float32(0.0), np.float32(0.439), np.float32(0.7667), np.float32(0.8082), np.float32(0.6949), np.float32(0.565), np.float32(0.0), np.float32(0.0), np.float32(0.8361), np.float32(0.6771), np.float32(0.8446), np.float32(0.7148), np.float32(0.4526), np.float32(0.7933), np.float32(0.9262), np.float32(0.9196), np.float32(0.6596), np.float32(0.6638), np.float32(0.4585), np.float32(0.8128), np.float32(0.691), np.float32(0.7343), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.952), np.float32(0.9689)] 
+2026-10-18 23:03:16.176094: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 23:03:16.487261: lr: 0.000827 
+2026-10-18 23:03:16.487536: This epoch took 279.692013 s
+ 
+2026-10-18 23:03:16.487630: 
+epoch:  190 
+2026-10-18 23:07:41.330537: train loss : -0.7791 
+2026-10-18 23:07:46.684095: validation loss: -0.6836 
+2026-10-18 23:07:46.685031: Average global foreground Dice: [np.float32(0.9384), np.float32(0.6995), np.float32(0.8283), np.float32(0.8618), np.float32(0.8122), np.float32(0.9248), np.float32(0.866), np.float32(0.1188), np.float32(0.0), np.float32(0.5036), np.float32(0.7362), np.float32(0.7858), np.float32(0.7273), np.float32(0.638), np.float32(0.0), np.float32(0.0), np.float32(0.8325), np.float32(0.6609), np.float32(0.8371), np.float32(0.6777), np.float32(0.4316), np.float32(0.7281), np.float32(0.9067), np.float32(0.9129), np.float32(0.6074), np.float32(0.6767), np.float32(0.4416), np.float32(0.85), np.float32(0.5976), np.float32(0.5831), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9461), np.float32(0.9661)] 
+2026-10-18 23:07:46.685198: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 23:07:46.970660: lr: 0.000826 
+2026-10-18 23:07:46.970984: This epoch took 270.483261 s
+ 
+2026-10-18 23:07:46.971100: 
+epoch:  191 
+2026-10-18 23:12:17.316086: train loss : -0.7678 
+2026-10-18 23:12:22.687801: validation loss: -0.6932 
+2026-10-18 23:12:22.688944: Average global foreground Dice: [np.float32(0.945), np.float32(0.7079), np.float32(0.8763), np.float32(0.8792), np.float32(0.8063), np.float32(0.9359), np.float32(0.8846), np.float32(0.4655), np.float32(0.0), np.float32(0.6176), np.float32(0.7842), np.float32(0.8472), np.float32(0.7387), np.float32(0.5781), np.float32(0.0), np.float32(0.0), np.float32(0.8348), np.float32(0.6905), np.float32(0.8464), np.float32(0.7287), np.float32(0.4214), np.float32(0.7987), np.float32(0.9086), np.float32(0.9042), np.float32(0.6993), np.float32(0.6987), np.float32(0.3725), np.float32(0.0012), np.float32(0.6299), np.float32(0.7058), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.945), np.float32(0.946)] 
+2026-10-18 23:12:22.689496: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 23:12:22.993108: lr: 0.000825 
+2026-10-18 23:12:22.993537: This epoch took 276.022375 s
+ 
+2026-10-18 23:12:22.993818: 
+epoch:  192 
+2026-10-18 23:16:23.590406: train loss : -0.7837 
+2026-10-18 23:16:28.940973: validation loss: -0.7068 
+2026-10-18 23:16:28.942046: Average global foreground Dice: [np.float32(0.9434), np.float32(0.7298), np.float32(0.8422), np.float32(0.8604), np.float32(0.8083), np.float32(0.9241), np.float32(0.8941), np.float32(0.604), np.float32(0.0), np.float32(0.5396), np.float32(0.7834), np.float32(0.808), np.float32(0.7144), np.float32(0.6319), np.float32(0.0), np.float32(0.0), np.float32(0.8167), np.float32(0.6058), np.float32(0.8241), np.float32(0.6666), np.float32(0.2255), np.float32(0.7687), np.float32(0.9128), np.float32(0.9149), np.float32(0.643), np.float32(0.641), np.float32(0.4595), np.float32(0.775), np.float32(0.6095), np.float32(0.7511), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9509), np.float32(0.9638)] 
+2026-10-18 23:16:28.942433: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 23:16:29.245904: lr: 0.000824 
+2026-10-18 23:16:29.246287: This epoch took 246.252202 s
+ 
+2026-10-18 23:16:29.246544: 
+epoch:  193 
+2026-10-18 23:20:47.305391: train loss : -0.7726 
+2026-10-18 23:20:52.649301: validation loss: -0.6860 
+2026-10-18 23:20:52.650363: Average global foreground Dice: [np.float32(0.9485), np.float32(0.7169), np.float32(0.8602), np.float32(0.8849), np.float32(0.8282), np.float32(0.9373), np.float32(0.8855), np.float32(0.6125), np.float32(0.0), np.float32(0.6245), np.float32(0.7805), np.float32(0.8187), np.float32(0.7229), np.float32(0.6177), np.float32(0.0), np.float32(0.0), np.float32(0.833), np.float32(0.6361), np.float32(0.8507), np.float32(0.7229), np.float32(0.4113), np.float32(0.7508), np.float32(0.9208), np.float32(0.918), np.float32(0.6394), np.float32(0.6672), np.float32(0.4462), np.float32(0.8529), np.float32(0.5463), np.float32(0.6879), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9614), np.float32(0.9687)] 
+2026-10-18 23:20:52.650957: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 23:20:52.940652: lr: 0.000824 
+2026-10-18 23:20:52.940998: This epoch took 263.694352 s
+ 
+2026-10-18 23:20:52.941234: 
+epoch:  194 
+2026-10-18 23:24:54.535450: train loss : -0.7813 
+2026-10-18 23:24:59.896645: validation loss: -0.6960 
+2026-10-18 23:24:59.897682: Average global foreground Dice: [np.float32(0.9163), np.float32(0.7282), np.float32(0.8536), np.float32(0.8756), np.float32(0.8242), np.float32(0.921), np.float32(0.8732), np.float32(0.5556), np.float32(0.0), np.float32(0.6151), np.float32(0.7711), np.float32(0.8233), np.float32(0.6912), np.float32(0.6195), np.float32(0.0), np.float32(0.0), np.float32(0.8333), np.float32(0.661), np.float32(0.8411), np.float32(0.7084), np.float32(0.3289), np.float32(0.7658), np.float32(0.9104), np.float32(0.9053), np.float32(0.6605), np.float32(0.6705), np.float32(0.4776), np.float32(0.778), np.float32(0.6197), np.float32(0.7189), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9508), np.float32(0.9629)] 
+2026-10-18 23:24:59.897963: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 23:25:00.197044: lr: 0.000823 
+2026-10-18 23:25:00.197537: This epoch took 247.256209 s
+ 
+2026-10-18 23:25:00.197774: 
+epoch:  195 
+2026-10-18 23:29:10.285990: train loss : -0.7796 
+2026-10-18 23:29:15.638142: validation loss: -0.6879 
+2026-10-18 23:29:15.639002: Average global foreground Dice: [np.float32(0.9412), np.float32(0.7265), np.float32(0.8583), np.float32(0.89), np.float32(0.8475), np.float32(0.9283), np.float32(0.8708), np.float32(0.4657), np.float32(0.0), np.float32(0.3846), np.float32(0.7595), np.float32(0.8203), np.float32(0.6936), np.float32(0.616), np.float32(0.0), np.float32(0.0), np.float32(0.8397), np.float32(0.688), np.float32(0.8367), np.float32(0.7065), np.float32(0.4367), np.float32(0.7612), np.float32(0.9186), np.float32(0.9252), np.float32(0.6245), np.float32(0.6653), np.float32(0.3956), np.float32(0.8578), np.float32(0.5964), np.float32(0.7316), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9497), np.float32(0.9668)] 
+2026-10-18 23:29:15.639145: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 23:29:15.930429: lr: 0.000822 
+2026-10-18 23:29:15.930812: This epoch took 255.732777 s
+ 
+2026-10-18 23:29:15.931064: 
+epoch:  196 
+2026-10-18 23:33:50.276873: train loss : -0.7745 
+2026-10-18 23:33:55.650614: validation loss: -0.6992 
+2026-10-18 23:33:55.651572: Average global foreground Dice: [np.float32(0.9475), np.float32(0.6801), np.float32(0.8549), np.float32(0.8858), np.float32(0.8071), np.float32(0.94), np.float32(0.8761), np.float32(0.6502), np.float32(0.0), np.float32(0.5891), np.float32(0.7855), np.float32(0.8376), np.float32(0.669), np.float32(0.5844), np.float32(0.0), np.float32(0.0), np.float32(0.8317), np.float32(0.6974), np.float32(0.8421), np.float32(0.715), np.float32(0.3461), np.float32(0.7358), np.float32(0.9116), np.float32(0.9215), np.float32(0.6325), np.float32(0.6871), np.float32(0.482), np.float32(0.8463), np.float32(0.5549), np.float32(0.7084), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9592), np.float32(0.9695)] 
+2026-10-18 23:33:55.651931: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 23:33:55.984124: lr: 0.000821 
+2026-10-18 23:33:55.984509: This epoch took 280.053226 s
+ 
+2026-10-18 23:33:55.984760: 
+epoch:  197 
+2026-10-18 23:38:13.393736: train loss : -0.7705 
+2026-10-18 23:38:18.732917: validation loss: -0.6971 
+2026-10-18 23:38:18.733805: Average global foreground Dice: [np.float32(0.9373), np.float32(0.7206), np.float32(0.849), np.float32(0.8724), np.float32(0.7837), np.float32(0.9368), np.float32(0.8793), np.float32(0.5555), np.float32(0.0), np.float32(0.4871), np.float32(0.7558), np.float32(0.8363), np.float32(0.6975), np.float32(0.6414), np.float32(0.0), np.float32(0.0), np.float32(0.8138), np.float32(0.6082), np.float32(0.8357), np.float32(0.6922), np.float32(0.391), np.float32(0.7902), np.float32(0.9258), np.float32(0.9143), np.float32(0.6435), np.float32(0.6544), np.float32(0.4689), np.float32(0.8482), np.float32(0.6402), np.float32(0.7151), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9438), np.float32(0.9689)] 
+2026-10-18 23:38:18.734037: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 23:38:19.024002: lr: 0.00082 
+2026-10-18 23:38:19.024271: This epoch took 263.039414 s
+ 
+2026-10-18 23:38:19.024354: 
+epoch:  198 
+2026-10-18 23:42:17.158098: train loss : -0.7732 
+2026-10-18 23:42:22.504905: validation loss: -0.6913 
+2026-10-18 23:42:22.505938: Average global foreground Dice: [np.float32(0.9442), np.float32(0.7419), np.float32(0.8518), np.float32(0.8775), np.float32(0.8147), np.float32(0.9336), np.float32(0.8798), np.float32(0.6207), np.float32(0.0), np.float32(0.1359), np.float32(0.7423), np.float32(0.8015), np.float32(0.6894), np.float32(0.618), np.float32(0.0), np.float32(0.0), np.float32(0.8184), np.float32(0.6389), np.float32(0.8408), np.float32(0.695), np.float32(0.388), np.float32(0.774), np.float32(0.925), np.float32(0.9274), np.float32(0.6793), np.float32(0.6683), np.float32(0.4439), np.float32(0.8614), np.float32(0.5831), np.float32(0.7346), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.951), np.float32(0.9633)] 
+2026-10-18 23:42:22.506249: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 23:42:22.810834: lr: 0.000819 
+2026-10-18 23:42:22.811062: This epoch took 243.786643 s
+ 
+2026-10-18 23:42:22.811142: 
+epoch:  199 
+2026-10-18 23:46:48.622427: train loss : -0.7731 
+2026-10-18 23:46:53.978774: validation loss: -0.7031 
+2026-10-18 23:46:53.979874: Average global foreground Dice: [np.float32(0.9366), np.float32(0.7504), np.float32(0.8543), np.float32(0.879), np.float32(0.8252), np.float32(0.9393), np.float32(0.8695), np.float32(0.6171), np.float32(0.0), np.float32(0.5542), np.float32(0.7606), np.float32(0.7996), np.float32(0.6627), np.float32(0.609), np.float32(0.0013), np.float32(0.0), np.float32(0.8303), np.float32(0.6577), np.float32(0.8418), np.float32(0.7082), np.float32(0.4979), np.float32(0.7997), np.float32(0.9293), np.float32(0.9213), np.float32(0.6492), np.float32(0.6766), np.float32(0.4559), np.float32(0.6465), np.float32(0.6851), np.float32(0.7454), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9564), np.float32(0.9684)] 
+2026-10-18 23:46:53.980034: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 23:46:54.272034: lr: 0.000818 
+2026-10-18 23:46:54.272301: saving scheduled checkpoint file... 
+2026-10-18 23:46:54.283474: saving checkpoint... 
+2026-10-18 23:46:54.412791: done, saving took 0.14 seconds 
+2026-10-18 23:46:54.414289: done 
+2026-10-18 23:46:54.414431: This epoch took 271.603235 s
+ 
+2026-10-18 23:46:54.414502: 
+epoch:  200 
+2026-10-18 23:51:13.395137: train loss : -0.7701 
+2026-10-18 23:51:18.744419: validation loss: -0.7047 
+2026-10-18 23:51:18.745429: Average global foreground Dice: [np.float32(0.9417), np.float32(0.7497), np.float32(0.8653), np.float32(0.8777), np.float32(0.8293), np.float32(0.9345), np.float32(0.8895), np.float32(0.6926), np.float32(0.0), np.float32(0.4471), np.float32(0.7519), np.float32(0.8367), np.float32(0.6965), np.float32(0.625), np.float32(0.0), np.float32(0.0), np.float32(0.8438), np.float32(0.695), np.float32(0.8502), np.float32(0.7142), np.float32(0.4038), np.float32(0.8012), np.float32(0.9409), np.float32(0.9353), np.float32(0.6661), np.float32(0.6728), np.float32(0.4492), np.float32(0.8478), np.float32(0.6604), np.float32(0.7571), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9555), np.float32(0.9702)] 
+2026-10-18 23:51:18.745831: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 23:51:19.052475: lr: 0.000817 
+2026-10-18 23:51:19.052732: This epoch took 264.638142 s
+ 
+2026-10-18 23:51:19.052826: 
+epoch:  201 
+2026-10-18 23:56:04.161944: train loss : -0.7721 
+2026-10-18 23:56:09.494664: validation loss: -0.7054 
+2026-10-18 23:56:09.495559: Average global foreground Dice: [np.float32(0.9431), np.float32(0.7285), np.float32(0.8645), np.float32(0.8863), np.float32(0.8123), np.float32(0.9392), np.float32(0.8782), np.float32(0.8158), np.float32(0.0), np.float32(0.3611), np.float32(0.7821), np.float32(0.84), np.float32(0.738), np.float32(0.6179), np.float32(0.0), np.float32(0.0), np.float32(0.8301), np.float32(0.6836), np.float32(0.8448), np.float32(0.6908), np.float32(0.3415), np.float32(0.795), np.float32(0.9307), np.float32(0.9315), np.float32(0.6524), np.float32(0.6791), np.float32(0.5286), np.float32(0.8859), np.float32(0.5833), np.float32(0.7706), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9616), np.float32(0.9701)] 
+2026-10-18 23:56:09.495771: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-18 23:56:09.790394: lr: 0.000816 
+2026-10-18 23:56:09.791241: This epoch took 290.738352 s
+ 
+2026-10-18 23:56:09.791654: 
+epoch:  202 
+2026-10-19 00:00:34.107084: train loss : -0.7776 
+2026-10-19 00:00:39.472617: validation loss: -0.7070 
+2026-10-19 00:00:39.473764: Average global foreground Dice: [np.float32(0.9267), np.float32(0.737), np.float32(0.8462), np.float32(0.8868), np.float32(0.8313), np.float32(0.9293), np.float32(0.8808), np.float32(0.7504), np.float32(0.0), np.float32(0.5999), np.float32(0.7521), np.float32(0.8013), np.float32(0.7204), np.float32(0.5225), np.float32(0.0), np.float32(0.0), np.float32(0.8318), np.float32(0.6896), np.float32(0.8418), np.float32(0.6978), np.float32(0.3735), np.float32(0.7389), np.float32(0.9149), np.float32(0.9117), np.float32(0.6989), np.float32(0.6611), np.float32(0.3536), np.float32(0.7976), np.float32(0.6349), np.float32(0.7798), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9615), np.float32(0.9699)] 
+2026-10-19 00:00:39.474018: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 00:00:39.774430: lr: 0.000815 
+2026-10-19 00:00:39.774885: This epoch took 269.982842 s
+ 
+2026-10-19 00:00:39.775030: 
+epoch:  203 
+2026-10-19 00:05:14.624839: train loss : -0.7667 
+2026-10-19 00:05:19.977230: validation loss: -0.6980 
+2026-10-19 00:05:19.978619: Average global foreground Dice: [np.float32(0.9343), np.float32(0.7053), np.float32(0.867), np.float32(0.8631), np.float32(0.8052), np.float32(0.9378), np.float32(0.8736), np.float32(0.2981), np.float32(0.0), np.float32(0.5627), np.float32(0.7623), np.float32(0.843), np.float32(0.7101), np.float32(0.5905), np.float32(0.0), np.float32(0.0), np.float32(0.8291), np.float32(0.6207), np.float32(0.8364), np.float32(0.7075), np.float32(0.3078), np.float32(0.7718), np.float32(0.9042), np.float32(0.9293), np.float32(0.6537), np.float32(0.7063), np.float32(0.4156), np.float32(0.8956), np.float32(0.5693), np.float32(0.7421), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9512), np.float32(0.9705)] 
+2026-10-19 00:05:19.978858: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 00:05:20.283715: lr: 0.000814 
+2026-10-19 00:05:20.284363: This epoch took 280.509242 s
+ 
+2026-10-19 00:05:20.284672: 
+epoch:  204 
+2026-10-19 00:09:48.956143: train loss : -0.7699 
+2026-10-19 00:09:54.315038: validation loss: -0.7075 
+2026-10-19 00:09:54.315976: Average global foreground Dice: [np.float32(0.9345), np.float32(0.7366), np.float32(0.862), np.float32(0.8807), np.float32(0.8182), np.float32(0.9318), np.float32(0.87), np.float32(0.8534), np.float32(0.0), np.float32(0.5701), np.float32(0.8021), np.float32(0.8272), np.float32(0.6694), np.float32(0.6138), np.float32(0.0), np.float32(0.0), np.float32(0.8212), np.float32(0.6435), np.float32(0.8421), np.float32(0.6936), np.float32(0.2912), np.float32(0.7892), np.float32(0.9239), np.float32(0.9109), np.float32(0.6641), np.float32(0.6586), np.float32(0.4308), np.float32(0.8448), np.float32(0.645), np.float32(0.7801), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9507), np.float32(0.9678)] 
+2026-10-19 00:09:54.316155: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 00:09:54.601643: lr: 0.000813 
+2026-10-19 00:09:54.601886: This epoch took 274.317036 s
+ 
+2026-10-19 00:09:54.601966: 
+epoch:  205 
+2026-10-19 00:14:31.085844: train loss : -0.7771 
+2026-10-19 00:14:36.469319: validation loss: -0.7111 
+2026-10-19 00:14:36.470502: Average global foreground Dice: [np.float32(0.9445), np.float32(0.7469), np.float32(0.8776), np.float32(0.8924), np.float32(0.8327), np.float32(0.94), np.float32(0.887), np.float32(0.7122), np.float32(0.0), np.float32(0.5619), np.float32(0.7813), np.float32(0.8401), np.float32(0.7201), np.float32(0.6056), np.float32(0.0), np.float32(0.0), np.float32(0.8389), np.float32(0.679), np.float32(0.848), np.float32(0.742), np.float32(0.4368), np.float32(0.8189), np.float32(0.931), np.float32(0.9187), np.float32(0.6886), np.float32(0.6983), np.float32(0.502), np.float32(0.8899), np.float32(0.687), np.float32(0.7627), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9581), np.float32(0.9706)] 
+2026-10-19 00:14:36.470790: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 00:14:36.764772: lr: 0.000813 
+2026-10-19 00:14:36.773457: saving checkpoint... 
+2026-10-19 00:14:36.900646: done, saving took 0.14 seconds 
+2026-10-19 00:14:36.902639: This epoch took 282.300615 s
+ 
+2026-10-19 00:14:36.902758: 
+epoch:  206 
+2026-10-19 00:18:46.724060: train loss : -0.7807 
+2026-10-19 00:18:52.103070: validation loss: -0.7037 
+2026-10-19 00:18:52.104060: Average global foreground Dice: [np.float32(0.933), np.float32(0.7281), np.float32(0.8722), np.float32(0.8792), np.float32(0.817), np.float32(0.9363), np.float32(0.8761), np.float32(0.6208), np.float32(0.0), np.float32(0.6188), np.float32(0.7795), np.float32(0.8565), np.float32(0.7189), np.float32(0.5717), np.float32(0.0), np.float32(0.0117), np.float32(0.8166), np.float32(0.6451), np.float32(0.8335), np.float32(0.6826), np.float32(0.3439), np.float32(0.7994), np.float32(0.9225), np.float32(0.9094), np.float32(0.6689), np.float32(0.6669), np.float32(0.4539), np.float32(0.8528), np.float32(0.645), np.float32(0.7591), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9551), np.float32(0.9692)] 
+2026-10-19 00:18:52.104220: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 00:18:52.395969: lr: 0.000812 
+2026-10-19 00:18:52.425849: saving checkpoint... 
+2026-10-19 00:18:52.579086: done, saving took 0.18 seconds 
+2026-10-19 00:18:52.580632: This epoch took 255.677812 s
+ 
+2026-10-19 00:18:52.580798: 
+epoch:  207 
+2026-10-19 00:23:03.811234: train loss : -0.7799 
+2026-10-19 00:23:09.193835: validation loss: -0.6958 
+2026-10-19 00:23:09.194990: Average global foreground Dice: [np.float32(0.9434), np.float32(0.7458), np.float32(0.8828), np.float32(0.8908), np.float32(0.8397), np.float32(0.9376), np.float32(0.8973), np.float32(0.4499), np.float32(0.0), np.float32(0.493), np.float32(0.7704), np.float32(0.8535), np.float32(0.6951), np.float32(0.5666), np.float32(0.0), np.float32(0.0), np.float32(0.8222), np.float32(0.6752), np.float32(0.8431), np.float32(0.7011), np.float32(0.329), np.float32(0.7574), np.float32(0.9321), np.float32(0.9172), np.float32(0.6421), np.float32(0.694), np.float32(0.475), np.float32(0.8002), np.float32(0.6684), np.float32(0.7475), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9574), np.float32(0.9682)] 
+2026-10-19 00:23:09.195400: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 00:23:09.485040: lr: 0.000811 
+2026-10-19 00:23:09.485635: This epoch took 256.904763 s
+ 
+2026-10-19 00:23:09.486063: 
+epoch:  208 
+2026-10-19 00:27:43.911501: train loss : -0.7787 
+2026-10-19 00:27:49.280366: validation loss: -0.6919 
+2026-10-19 00:27:49.281619: Average global foreground Dice: [np.float32(0.9164), np.float32(0.7071), np.float32(0.866), np.float32(0.8636), np.float32(0.791), np.float32(0.9389), np.float32(0.8876), np.float32(0.7838), np.float32(0.0), np.float32(0.585), np.float32(0.7716), np.float32(0.8378), np.float32(0.6555), np.float32(0.5537), np.float32(0.0044), np.float32(0.0), np.float32(0.8278), np.float32(0.6219), np.float32(0.8345), np.float32(0.6299), np.float32(0.2511), np.float32(0.7922), np.float32(0.9021), np.float32(0.8906), np.float32(0.573), np.float32(0.6491), np.float32(0.2931), np.float32(0.4873), np.float32(0.6189), np.float32(0.7175), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9546), np.float32(0.9655)] 
+2026-10-19 00:27:49.282068: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 00:27:49.569796: lr: 0.00081 
+2026-10-19 00:27:49.570250: This epoch took 280.083963 s
+ 
+2026-10-19 00:27:49.570506: 
+epoch:  209 
+2026-10-19 00:32:06.763922: train loss : -0.7788 
+2026-10-19 00:32:12.123046: validation loss: -0.6888 
+2026-10-19 00:32:12.123994: Average global foreground Dice: [np.float32(0.9466), np.float32(0.7403), np.float32(0.8604), np.float32(0.872), np.float32(0.8107), np.float32(0.933), np.float32(0.8803), np.float32(0.7174), np.float32(0.0), np.float32(0.5011), np.float32(0.7656), np.float32(0.8178), np.float32(0.6809), np.float32(0.5295), np.float32(0.0), np.float32(0.0), np.float32(0.8355), np.float32(0.6776), np.float32(0.8515), np.float32(0.727), np.float32(0.3757), np.float32(0.7564), np.float32(0.9289), np.float32(0.9168), np.float32(0.6387), np.float32(0.7015), np.float32(0.4151), np.float32(0.8074), np.float32(0.6745), np.float32(0.5949), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9542), np.float32(0.9692)] 
+2026-10-19 00:32:12.124252: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 00:32:12.418750: lr: 0.000809 
+2026-10-19 00:32:12.419189: This epoch took 262.848573 s
+ 
+2026-10-19 00:32:12.419494: 
+epoch:  210 
+2026-10-19 00:36:09.326226: train loss : -0.7757 
+2026-10-19 00:36:14.686763: validation loss: -0.6901 
+2026-10-19 00:36:14.687910: Average global foreground Dice: [np.float32(0.9463), np.float32(0.7212), np.float32(0.8812), np.float32(0.8848), np.float32(0.8232), np.float32(0.9322), np.float32(0.8814), np.float32(0.8332), np.float32(0.0111), np.float32(0.3153), np.float32(0.7182), np.float32(0.8222), np.float32(0.6538), np.float32(0.5709), np.float32(0.0056), np.float32(0.0), np.float32(0.834), np.float32(0.667), np.float32(0.8452), np.float32(0.7183), np.float32(0.3392), np.float32(0.7698), np.float32(0.9346), np.float32(0.9351), np.float32(0.6194), np.float32(0.7052), np.float32(0.4388), np.float32(0.8737), np.float32(0.6227), np.float32(0.7607), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9617), np.float32(0.9697)] 
+2026-10-19 00:36:14.688305: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 00:36:14.983130: lr: 0.000808 
+2026-10-19 00:36:14.983571: This epoch took 242.563869 s
+ 
+2026-10-19 00:36:14.983757: 
+epoch:  211 
+2026-10-19 00:40:46.401353: train loss : -0.7713 
+2026-10-19 00:40:51.763377: validation loss: -0.7151 
+2026-10-19 00:40:51.764436: Average global foreground Dice: [np.float32(0.9472), np.float32(0.7511), np.float32(0.8663), np.float32(0.8831), np.float32(0.8328), np.float32(0.9363), np.float32(0.8921), np.float32(0.5122), np.float32(0.0), np.float32(0.58), np.float32(0.7894), np.float32(0.8479), np.float32(0.707), np.float32(0.5973), np.float32(0.0), np.float32(0.0), np.float32(0.8181), np.float32(0.6573), np.float32(0.8216), np.float32(0.6791), np.float32(0.2906), np.float32(0.7836), np.float32(0.9331), np.float32(0.9302), np.float32(0.6081), np.float32(0.6504), np.float32(0.501), np.float32(0.819), np.float32(0.6839), np.float32(0.7624), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9583), np.float32(0.969)] 
+2026-10-19 00:40:51.764724: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 00:40:52.077754: lr: 0.000807 
+2026-10-19 00:40:52.078258: This epoch took 277.094438 s
+ 
+2026-10-19 00:40:52.078401: 
+epoch:  212 
+2026-10-19 00:45:29.291116: train loss : -0.7712 
+2026-10-19 00:45:34.661605: validation loss: -0.7172 
+2026-10-19 00:45:34.662713: Average global foreground Dice: [np.float32(0.9474), np.float32(0.7711), np.float32(0.8703), np.float32(0.8913), np.float32(0.8434), np.float32(0.9395), np.float32(0.8746), np.float32(0.7659), np.float32(0.0), np.float32(0.6017), np.float32(0.7736), np.float32(0.8419), np.float32(0.6977), np.float32(0.5977), np.float32(0.0), np.float32(0.0), np.float32(0.8356), np.float32(0.6949), np.float32(0.8342), np.float32(0.7381), np.float32(0.406), np.float32(0.7599), np.float32(0.9344), np.float32(0.9376), np.float32(0.7168), np.float32(0.6786), np.float32(0.4475), np.float32(0.852), np.float32(0.6996), np.float32(0.8136), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9596), np.float32(0.969)] 
+2026-10-19 00:45:34.662951: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 00:45:34.951696: lr: 0.000806 
+2026-10-19 00:45:34.961392: saving checkpoint... 
+2026-10-19 00:45:35.845370: done, saving took 0.89 seconds 
+2026-10-19 00:45:35.847753: This epoch took 283.769274 s
+ 
+2026-10-19 00:45:35.848085: 
+epoch:  213 
+2026-10-19 00:50:03.221028: train loss : -0.7731 
+2026-10-19 00:50:08.582689: validation loss: -0.6939 
+2026-10-19 00:50:08.583784: Average global foreground Dice: [np.float32(0.9465), np.float32(0.7085), np.float32(0.8718), np.float32(0.8908), np.float32(0.8412), np.float32(0.9299), np.float32(0.8753), np.float32(0.8194), np.float32(0.0), np.float32(0.0), np.float32(0.7689), np.float32(0.823), np.float32(0.6778), np.float32(0.6387), np.float32(0.0), np.float32(0.0), np.float32(0.8373), np.float32(0.6743), np.float32(0.853), np.float32(0.7398), np.float32(0.2748), np.float32(0.7846), np.float32(0.935), np.float32(0.917), np.float32(0.6352), np.float32(0.7074), np.float32(0.4247), np.float32(0.7583), np.float32(0.621), np.float32(0.743), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9505), np.float32(0.9691)] 
+2026-10-19 00:50:08.583981: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 00:50:08.879148: lr: 0.000805 
+2026-10-19 00:50:08.879446: This epoch took 273.031182 s
+ 
+2026-10-19 00:50:08.879687: 
+epoch:  214 
+2026-10-19 00:54:20.951466: train loss : -0.7619 
+2026-10-19 00:54:26.303024: validation loss: -0.6921 
+2026-10-19 00:54:26.304127: Average global foreground Dice: [np.float32(0.9368), np.float32(0.7216), np.float32(0.8331), np.float32(0.8816), np.float32(0.8331), np.float32(0.9281), np.float32(0.8795), np.float32(0.5453), np.float32(0.0), np.float32(0.4893), np.float32(0.7677), np.float32(0.8475), np.float32(0.6799), np.float32(0.6009), np.float32(0.0), np.float32(0.0), np.float32(0.8256), np.float32(0.6565), np.float32(0.826), np.float32(0.6938), np.float32(0.4095), np.float32(0.7939), np.float32(0.9064), np.float32(0.9026), np.float32(0.6319), np.float32(0.6159), np.float32(0.4398), np.float32(0.8217), np.float32(0.6569), np.float32(0.6585), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9546), np.float32(0.9674)] 
+2026-10-19 00:54:26.304352: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 00:54:26.610735: lr: 0.000804 
+2026-10-19 00:54:26.610970: This epoch took 257.731096 s
+ 
+2026-10-19 00:54:26.611046: 
+epoch:  215 
+2026-10-19 00:59:26.572216: train loss : -0.7737 
+2026-10-19 00:59:31.924333: validation loss: -0.6957 
+2026-10-19 00:59:31.925268: Average global foreground Dice: [np.float32(0.938), np.float32(0.7217), np.float32(0.8667), np.float32(0.8726), np.float32(0.8219), np.float32(0.9304), np.float32(0.8639), np.float32(0.4861), np.float32(0.0), np.float32(0.4438), np.float32(0.7651), np.float32(0.8444), np.float32(0.7001), np.float32(0.6529), np.float32(0.001), np.float32(0.0), np.float32(0.8299), np.float32(0.6592), np.float32(0.8322), np.float32(0.7099), np.float32(0.3919), np.float32(0.7721), np.float32(0.9287), np.float32(0.9267), np.float32(0.6287), np.float32(0.7017), np.float32(0.4469), np.float32(0.7854), np.float32(0.6218), np.float32(0.6893), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9589), np.float32(0.9651)] 
+2026-10-19 00:59:31.925511: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 00:59:32.249642: lr: 0.000803 
+2026-10-19 00:59:32.250003: This epoch took 305.638900 s
+ 
+2026-10-19 00:59:32.250217: 
+epoch:  216 
+2026-10-19 01:03:53.392269: train loss : -0.7813 
+2026-10-19 01:03:58.736174: validation loss: -0.7010 
+2026-10-19 01:03:58.737432: Average global foreground Dice: [np.float32(0.9376), np.float32(0.6965), np.float32(0.853), np.float32(0.8719), np.float32(0.8143), np.float32(0.9384), np.float32(0.8868), np.float32(0.5594), np.float32(0.0), np.float32(0.3145), np.float32(0.7335), np.float32(0.8097), np.float32(0.7006), np.float32(0.6733), np.float32(0.0), np.float32(0.0), np.float32(0.8218), np.float32(0.6336), np.float32(0.8398), np.float32(0.6969), np.float32(0.3024), np.float32(0.784), np.float32(0.9255), np.float32(0.9228), np.float32(0.6056), np.float32(0.6657), np.float32(0.4659), np.float32(0.8268), np.float32(0.5738), np.float32(0.7546), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9579), np.float32(0.9661)] 
+2026-10-19 01:03:58.737785: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 01:03:59.042304: lr: 0.000802 
+2026-10-19 01:03:59.042792: This epoch took 266.792485 s
+ 
+2026-10-19 01:03:59.042992: 
+epoch:  217 
+2026-10-19 01:08:45.110155: train loss : -0.7782 
+2026-10-19 01:08:50.457586: validation loss: -0.7037 
+2026-10-19 01:08:50.458789: Average global foreground Dice: [np.float32(0.9444), np.float32(0.7348), np.float32(0.8627), np.float32(0.8816), np.float32(0.8247), np.float32(0.9371), np.float32(0.8922), np.float32(0.5906), np.float32(0.0), np.float32(0.5275), np.float32(0.7619), np.float32(0.8252), np.float32(0.7316), np.float32(0.5802), np.float32(0.0442), np.float32(0.0), np.float32(0.8294), np.float32(0.6565), np.float32(0.8394), np.float32(0.7036), np.float32(0.3574), np.float32(0.7812), np.float32(0.9245), np.float32(0.9266), np.float32(0.658), np.float32(0.6762), np.float32(0.4047), np.float32(0.7533), np.float32(0.5966), np.float32(0.7048), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9569), np.float32(0.97)] 
+2026-10-19 01:08:50.459156: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 01:08:50.778795: lr: 0.000801 
+2026-10-19 01:08:50.779247: This epoch took 291.736170 s
+ 
+2026-10-19 01:08:50.779579: 
+epoch:  218 
+2026-10-19 01:12:58.378153: train loss : -0.7828 
+2026-10-19 01:13:03.736589: validation loss: -0.7127 
+2026-10-19 01:13:03.737715: Average global foreground Dice: [np.float32(0.9411), np.float32(0.7484), np.float32(0.8547), np.float32(0.8874), np.float32(0.8307), np.float32(0.9301), np.float32(0.8786), np.float32(0.6316), np.float32(0.0), np.float32(0.5148), np.float32(0.7525), np.float32(0.7973), np.float32(0.7386), np.float32(0.6312), np.float32(0.0233), np.float32(0.0), np.float32(0.8391), np.float32(0.6726), np.float32(0.8347), np.float32(0.7233), np.float32(0.3972), np.float32(0.8032), np.float32(0.9158), np.float32(0.9015), np.float32(0.6585), np.float32(0.6803), np.float32(0.383), np.float32(0.8768), np.float32(0.6104), np.float32(0.6897), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9577), np.float32(0.9629)] 
+2026-10-19 01:13:03.738087: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 01:13:04.029571: lr: 0.000801 
+2026-10-19 01:13:04.029989: This epoch took 253.250194 s
+ 
+2026-10-19 01:13:04.030396: 
+epoch:  219 
+2026-10-19 01:17:21.011614: train loss : -0.7771 
+2026-10-19 01:17:26.369715: validation loss: -0.7047 
+2026-10-19 01:17:26.370585: Average global foreground Dice: [np.float32(0.9464), np.float32(0.721), np.float32(0.8656), np.float32(0.8975), np.float32(0.8074), np.float32(0.9324), np.float32(0.8982), np.float32(0.7564), np.float32(0.0), np.float32(0.4354), np.float32(0.788), np.float32(0.8274), np.float32(0.7168), np.float32(0.6142), np.float32(0.0617), np.float32(0.0), np.float32(0.833), np.float32(0.6851), np.float32(0.8508), np.float32(0.7274), np.float32(0.3893), np.float32(0.8258), np.float32(0.9215), np.float32(0.9299), np.float32(0.6459), np.float32(0.6999), np.float32(0.3607), np.float32(0.868), np.float32(0.5686), np.float32(0.7501), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9593), np.float32(0.9685)] 
+2026-10-19 01:17:26.370732: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 01:17:26.650980: lr: 0.0008 
+2026-10-19 01:17:26.651356: This epoch took 262.620842 s
+ 
+2026-10-19 01:17:26.651635: 
+epoch:  220 
+2026-10-19 01:21:25.573858: train loss : -0.7868 
+2026-10-19 01:21:30.914618: validation loss: -0.7086 
+2026-10-19 01:21:30.915763: Average global foreground Dice: [np.float32(0.9415), np.float32(0.7444), np.float32(0.883), np.float32(0.8907), np.float32(0.8054), np.float32(0.9334), np.float32(0.8955), np.float32(0.813), np.float32(0.0), np.float32(0.5042), np.float32(0.7636), np.float32(0.8381), np.float32(0.745), np.float32(0.6142), np.float32(0.0), np.float32(0.0), np.float32(0.8304), np.float32(0.69), np.float32(0.8444), np.float32(0.7376), np.float32(0.3992), np.float32(0.809), np.float32(0.9291), np.float32(0.9332), np.float32(0.6699), np.float32(0.6879), np.float32(0.3796), np.float32(0.8736), np.float32(0.6444), np.float32(0.779), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.959), np.float32(0.9689)] 
+2026-10-19 01:21:30.916001: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 01:21:31.214155: lr: 0.000799 
+2026-10-19 01:21:31.214588: This epoch took 244.562835 s
+ 
+2026-10-19 01:21:31.214698: 
+epoch:  221 
+2026-10-19 01:25:26.838999: train loss : -0.7859 
+2026-10-19 01:25:32.221185: validation loss: -0.6790 
+2026-10-19 01:25:32.222338: Average global foreground Dice: [np.float32(0.9402), np.float32(0.6755), np.float32(0.8867), np.float32(0.866), np.float32(0.7602), np.float32(0.9266), np.float32(0.8775), np.float32(0.7044), np.float32(0.0), np.float32(0.3049), np.float32(0.7285), np.float32(0.829), np.float32(0.6936), np.float32(0.5881), np.float32(0.0), np.float32(0.0), np.float32(0.8147), np.float32(0.6427), np.float32(0.8393), np.float32(0.6767), np.float32(0.2397), np.float32(0.769), np.float32(0.921), np.float32(0.9246), np.float32(0.621), np.float32(0.7026), np.float32(0.2858), np.float32(0.8371), np.float32(0.5329), np.float32(0.74), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9583), np.float32(0.9688)] 
+2026-10-19 01:25:32.222747: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 01:25:32.531547: lr: 0.000798 
+2026-10-19 01:25:32.531920: This epoch took 241.317160 s
+ 
+2026-10-19 01:25:32.532110: 
+epoch:  222 
+2026-10-19 01:30:18.732224: train loss : -0.7801 
+2026-10-19 01:30:24.105664: validation loss: -0.7121 
+2026-10-19 01:30:24.106684: Average global foreground Dice: [np.float32(0.9407), np.float32(0.7237), np.float32(0.873), np.float32(0.8863), np.float32(0.8037), np.float32(0.9404), np.float32(0.8941), np.float32(0.6089), np.float32(0.0), np.float32(0.48), np.float32(0.7713), np.float32(0.818), np.float32(0.75), np.float32(0.6201), np.float32(0.2724), np.float32(0.0), np.float32(0.8366), np.float32(0.6988), np.float32(0.8486), np.float32(0.7128), np.float32(0.3199), np.float32(0.7909), np.float32(0.9302), np.float32(0.92), np.float32(0.6212), np.float32(0.6817), np.float32(0.3921), np.float32(0.8781), np.float32(0.6747), np.float32(0.76), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9589), np.float32(0.9711)] 
+2026-10-19 01:30:24.107101: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 01:30:24.396531: lr: 0.000797 
+2026-10-19 01:30:24.397508: This epoch took 291.865323 s
+ 
+2026-10-19 01:30:24.398758: 
+epoch:  223 
+2026-10-19 01:34:36.378182: train loss : -0.7879 
+2026-10-19 01:34:41.754937: validation loss: -0.7261 
+2026-10-19 01:34:41.755887: Average global foreground Dice: [np.float32(0.9428), np.float32(0.7786), np.float32(0.8747), np.float32(0.9036), np.float32(0.8646), np.float32(0.9338), np.float32(0.8936), np.float32(0.5937), np.float32(0.0), np.float32(0.5549), np.float32(0.7762), np.float32(0.8378), np.float32(0.7629), np.float32(0.5914), np.float32(0.0225), np.float32(0.0), np.float32(0.8329), np.float32(0.662), np.float32(0.8475), np.float32(0.7), np.float32(0.2968), np.float32(0.8168), np.float32(0.9378), np.float32(0.9146), np.float32(0.6471), np.float32(0.6618), np.float32(0.3774), np.float32(0.8662), np.float32(0.6781), np.float32(0.7844), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.953), np.float32(0.9681)] 
+2026-10-19 01:34:41.756335: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 01:34:42.059537: lr: 0.000796 
+2026-10-19 01:34:42.060013: This epoch took 257.660860 s
+ 
+2026-10-19 01:34:42.060328: 
+epoch:  224 
+2026-10-19 01:38:58.045759: train loss : -0.7822 
+2026-10-19 01:39:03.399313: validation loss: -0.7079 
+2026-10-19 01:39:03.400979: Average global foreground Dice: [np.float32(0.9324), np.float32(0.7492), np.float32(0.8664), np.float32(0.8714), np.float32(0.8217), np.float32(0.9365), np.float32(0.894), np.float32(0.8164), np.float32(0.0), np.float32(0.5668), np.float32(0.7845), np.float32(0.854), np.float32(0.7055), np.float32(0.5895), np.float32(0.0508), np.float32(0.0), np.float32(0.8257), np.float32(0.5993), np.float32(0.8287), np.float32(0.6571), np.float32(0.3242), np.float32(0.7607), np.float32(0.9138), np.float32(0.8972), np.float32(0.6689), np.float32(0.6488), np.float32(0.5003), np.float32(0.7281), np.float32(0.5992), np.float32(0.7757), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9578), np.float32(0.9686)] 
+2026-10-19 01:39:03.401240: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 01:39:03.749750: lr: 0.000795 
+2026-10-19 01:39:03.758354: saving checkpoint... 
+2026-10-19 01:39:03.887949: done, saving took 0.14 seconds 
+2026-10-19 01:39:03.889435: This epoch took 261.828874 s
+ 
+2026-10-19 01:39:03.889723: 
+epoch:  225 
+2026-10-19 01:43:02.499769: train loss : -0.7795 
+2026-10-19 01:43:07.846824: validation loss: -0.7023 
+2026-10-19 01:43:07.848164: Average global foreground Dice: [np.float32(0.9439), np.float32(0.6869), np.float32(0.8664), np.float32(0.8815), np.float32(0.8048), np.float32(0.9363), np.float32(0.8815), np.float32(0.7123), np.float32(0.0), np.float32(0.5202), np.float32(0.7701), np.float32(0.831), np.float32(0.7366), np.float32(0.608), np.float32(0.0599), np.float32(0.0), np.float32(0.8355), np.float32(0.6806), np.float32(0.844), np.float32(0.7259), np.float32(0.3728), np.float32(0.8105), np.float32(0.9323), np.float32(0.9288), np.float32(0.6059), np.float32(0.7074), np.float32(0.4018), np.float32(0.8523), np.float32(0.5898), np.float32(0.7171), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9621), np.float32(0.9691)] 
+2026-10-19 01:43:07.848507: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 01:43:08.173219: lr: 0.000794 
+2026-10-19 01:43:08.205000: saving checkpoint... 
+2026-10-19 01:43:08.350889: done, saving took 0.18 seconds 
+2026-10-19 01:43:08.352373: This epoch took 244.462436 s
+ 
+2026-10-19 01:43:08.352513: 
+epoch:  226 
+2026-10-19 01:47:24.340679: train loss : -0.7800 
+2026-10-19 01:47:29.692992: validation loss: -0.7050 
+2026-10-19 01:47:29.693881: Average global foreground Dice: [np.float32(0.9467), np.float32(0.7253), np.float32(0.8809), np.float32(0.884), np.float32(0.8236), np.float32(0.9369), np.float32(0.8892), np.float32(0.7129), np.float32(0.0), np.float32(0.5021), np.float32(0.7929), np.float32(0.8348), np.float32(0.7235), np.float32(0.6529), np.float32(0.0015), np.float32(0.0), np.float32(0.8265), np.float32(0.6895), np.float32(0.8417), np.float32(0.7395), np.float32(0.2532), np.float32(0.8287), np.float32(0.9316), np.float32(0.9253), np.float32(0.6458), np.float32(0.6767), np.float32(0.3763), np.float32(0.7805), np.float32(0.5791), np.float32(0.7102), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9538), np.float32(0.9689)] 
+2026-10-19 01:47:29.694031: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 01:47:29.990014: lr: 0.000793 
+2026-10-19 01:47:30.011173: saving checkpoint... 
+2026-10-19 01:47:30.155543: done, saving took 0.17 seconds 
+2026-10-19 01:47:30.157032: This epoch took 261.804450 s
+ 
+2026-10-19 01:47:30.157247: 
+epoch:  227 
+2026-10-19 01:51:54.146219: train loss : -0.7792 
+2026-10-19 01:51:59.492368: validation loss: -0.7102 
+2026-10-19 01:51:59.493864: Average global foreground Dice: [np.float32(0.9485), np.float32(0.7572), np.float32(0.8728), np.float32(0.8948), np.float32(0.8363), np.float32(0.9347), np.float32(0.8823), np.float32(0.6806), np.float32(0.0), np.float32(0.3514), np.float32(0.7704), np.float32(0.8123), np.float32(0.6731), np.float32(0.5704), np.float32(0.0), np.float32(0.0), np.float32(0.8398), np.float32(0.6791), np.float32(0.8478), np.float32(0.7088), np.float32(0.3131), np.float32(0.8133), np.float32(0.9349), np.float32(0.9383), np.float32(0.6818), np.float32(0.6714), np.float32(0.4212), np.float32(0.8714), np.float32(0.615), np.float32(0.7571), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9606), np.float32(0.9695)] 
+2026-10-19 01:51:59.494144: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 01:51:59.792388: lr: 0.000792 
+2026-10-19 01:51:59.792834: This epoch took 269.635501 s
+ 
+2026-10-19 01:51:59.793048: 
+epoch:  228 
+2026-10-19 01:56:21.356396: train loss : -0.7885 
+2026-10-19 01:56:26.718544: validation loss: -0.7123 
+2026-10-19 01:56:26.719675: Average global foreground Dice: [np.float32(0.9506), np.float32(0.7603), np.float32(0.8822), np.float32(0.8839), np.float32(0.8257), np.float32(0.9368), np.float32(0.8902), np.float32(0.7423), np.float32(0.0), np.float32(0.4225), np.float32(0.7662), np.float32(0.8007), np.float32(0.7166), np.float32(0.6034), np.float32(0.0397), np.float32(0.0), np.float32(0.8428), np.float32(0.6979), np.float32(0.8498), np.float32(0.7176), np.float32(0.3687), np.float32(0.824), np.float32(0.9374), np.float32(0.9353), np.float32(0.6942), np.float32(0.7039), np.float32(0.3939), np.float32(0.8592), np.float32(0.6472), np.float32(0.7576), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9625), np.float32(0.9701)] 
+2026-10-19 01:56:26.719861: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 01:56:27.031021: lr: 0.000791 
+2026-10-19 01:56:27.039936: saving checkpoint... 
+2026-10-19 01:56:27.168405: done, saving took 0.14 seconds 
+2026-10-19 01:56:27.169739: This epoch took 267.376608 s
+ 
+2026-10-19 01:56:27.169922: 
+epoch:  229 
+2026-10-19 02:00:58.031759: train loss : -0.7818 
+2026-10-19 02:01:03.388075: validation loss: -0.6957 
+2026-10-19 02:01:03.388972: Average global foreground Dice: [np.float32(0.9454), np.float32(0.7452), np.float32(0.8641), np.float32(0.8868), np.float32(0.8487), np.float32(0.9225), np.float32(0.8871), np.float32(0.6005), np.float32(0.0), np.float32(0.4305), np.float32(0.751), np.float32(0.8066), np.float32(0.6632), np.float32(0.4197), np.float32(0.0), np.float32(0.0), np.float32(0.831), np.float32(0.675), np.float32(0.8415), np.float32(0.7184), np.float32(0.4001), np.float32(0.8096), np.float32(0.8979), np.float32(0.8715), np.float32(0.6789), np.float32(0.6701), np.float32(0.4424), np.float32(0.8392), np.float32(0.6497), np.float32(0.5708), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9622), np.float32(0.9675)] 
+2026-10-19 02:01:03.389214: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 02:01:03.677823: lr: 0.00079 
+2026-10-19 02:01:03.678071: This epoch took 276.508065 s
+ 
+2026-10-19 02:01:03.678154: 
+epoch:  230 
+2026-10-19 02:05:17.481177: train loss : -0.7823 
+2026-10-19 02:05:22.821822: validation loss: -0.7148 
+2026-10-19 02:05:22.822931: Average global foreground Dice: [np.float32(0.9454), np.float32(0.7062), np.float32(0.8731), np.float32(0.8981), np.float32(0.8214), np.float32(0.9343), np.float32(0.8938), np.float32(0.8184), np.float32(0.0), np.float32(0.5577), np.float32(0.7978), np.float32(0.8441), np.float32(0.7041), np.float32(0.5965), np.float32(0.0123), np.float32(0.0), np.float32(0.825), np.float32(0.6467), np.float32(0.8453), np.float32(0.6918), np.float32(0.2511), np.float32(0.8188), np.float32(0.9321), np.float32(0.9268), np.float32(0.6328), np.float32(0.6771), np.float32(0.3925), np.float32(0.7833), np.float32(0.6321), np.float32(0.7932), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9526), np.float32(0.97)] 
+2026-10-19 02:05:22.823280: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 02:05:23.131299: lr: 0.000789 
+2026-10-19 02:05:23.131567: This epoch took 259.453361 s
+ 
+2026-10-19 02:05:23.131899: 
+epoch:  231 
+2026-10-19 02:09:44.967741: train loss : -0.7824 
+2026-10-19 02:09:50.311238: validation loss: -0.7010 
+2026-10-19 02:09:50.312282: Average global foreground Dice: [np.float32(0.9409), np.float32(0.7274), np.float32(0.8617), np.float32(0.8887), np.float32(0.7953), np.float32(0.9347), np.float32(0.8838), np.float32(0.7559), np.float32(0.0), np.float32(0.4838), np.float32(0.747), np.float32(0.8218), np.float32(0.7115), np.float32(0.6384), np.float32(0.0012), np.float32(0.0), np.float32(0.7971), np.float32(0.6129), np.float32(0.8174), np.float32(0.6883), np.float32(0.3673), np.float32(0.8136), np.float32(0.9249), np.float32(0.9115), np.float32(0.6329), np.float32(0.6802), np.float32(0.4295), np.float32(0.801), np.float32(0.6767), np.float32(0.7232), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.951), np.float32(0.9695)] 
+2026-10-19 02:09:50.312678: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 02:09:50.597688: lr: 0.000789 
+2026-10-19 02:09:50.598207: This epoch took 267.466198 s
+ 
+2026-10-19 02:09:50.598550: 
+epoch:  232 
+2026-10-19 02:14:02.857351: train loss : -0.7858 
+2026-10-19 02:14:08.207558: validation loss: -0.7018 
+2026-10-19 02:14:08.208771: Average global foreground Dice: [np.float32(0.9414), np.float32(0.724), np.float32(0.8654), np.float32(0.8947), np.float32(0.8287), np.float32(0.9322), np.float32(0.888), np.float32(0.8398), np.float32(0.0), np.float32(0.5036), np.float32(0.7607), np.float32(0.8204), np.float32(0.7189), np.float32(0.6369), np.float32(0.0413), np.float32(0.0), np.float32(0.8264), np.float32(0.6324), np.float32(0.8442), np.float32(0.6825), np.float32(0.2907), np.float32(0.7992), np.float32(0.9227), np.float32(0.9243), np.float32(0.6433), np.float32(0.6755), np.float32(0.4613), np.float32(0.8365), np.float32(0.6098), np.float32(0.7693), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.9544), np.float32(0.97)] 
+2026-10-19 02:14:08.209286: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 02:14:08.541096: lr: 0.000788 
+2026-10-19 02:14:08.541430: This epoch took 257.942602 s
+ 
+2026-10-19 02:14:08.541646: 
+epoch:  233 
+2026-10-19 02:18:24.742327: train loss : -0.7935 
+2026-10-19 02:18:30.101181: validation loss: -0.7105 
+2026-10-19 02:18:30.102119: Average global foreground Dice: [np.float32(0.9455), np.float32(0.6565), np.float32(0.8781), np.float32(0.9041), np.float32(0.8037), np.float32(0.9279), np.float32(0.8851), np.float32(0.7349), np.float32(0.0), np.float32(0.6017), np.float32(0.7623), np.float32(0.8546), np.float32(0.6923), np.float32(0.4751), np.float32(0.0005), np.float32(0.0), np.float32(0.8343), np.float32(0.6669), np.float32(0.8533), np.float32(0.7245), np.float32(0.2881), np.float32(0.8039), np.float32(0.9219), np.float32(0.9359), np.float32(0.6426), np.float32(0.6871), np.float32(0.4411), np.float32(0.8744), np.float32(0.5634), np.float32(0.7828), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.5971), np.float32(0.9585), np.float32(0.9675)] 
+2026-10-19 02:18:30.102382: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 02:18:30.436109: lr: 0.000787 
+2026-10-19 02:18:30.454990: saving checkpoint... 
+2026-10-19 02:18:30.582876: done, saving took 0.15 seconds 
+2026-10-19 02:18:30.584336: This epoch took 262.042563 s
+ 
+2026-10-19 02:18:30.584546: 
+epoch:  234 
+2026-10-19 02:22:58.970852: train loss : -0.7875 
+2026-10-19 02:23:04.325879: validation loss: -0.7272 
+2026-10-19 02:23:04.327307: Average global foreground Dice: [np.float32(0.9399), np.float32(0.7394), np.float32(0.8617), np.float32(0.8773), np.float32(0.8303), np.float32(0.9345), np.float32(0.8907), np.float32(0.6855), np.float32(0.0), np.float32(0.4514), np.float32(0.7772), np.float32(0.8547), np.float32(0.7031), np.float32(0.6531), np.float32(0.0), np.float32(0.0), np.float32(0.825), np.float32(0.6353), np.float32(0.839), np.float32(0.6934), np.float32(0.3059), np.float32(0.8223), np.float32(0.9067), np.float32(0.9008), np.float32(0.6321), np.float32(0.6528), np.float32(0.4515), np.float32(0.8377), np.float32(0.6429), np.float32(0.7721), np.float32(0.0), np.float32(0.0), np.float32(0.0), np.float32(0.5851), np.float32(0.9605), np.float32(0.9701)] 
+2026-10-19 02:23:04.327528: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 02:23:04.642398: lr: 0.000786 
+2026-10-19 02:23:04.674990: saving checkpoint... 
+2026-10-19 02:23:04.817781: done, saving took 0.18 seconds 
+2026-10-19 02:23:04.818958: This epoch took 274.234298 s
+ 
+2026-10-19 02:23:04.819132: 
+epoch:  235 
+2026-10-19 02:27:21.011258: train loss : -0.7975 
+2026-10-19 02:27:26.361073: validation loss: -0.7116 
+2026-10-19 02:27:26.362053: Average global foreground Dice: [np.float32(0.9399), np.float32(0.7445), np.float32(0.8567), np.float32(0.8835), np.float32(0.832), np.float32(0.933), np.float32(0.8826), np.float32(0.7937), np.float32(0.0), np.float32(0.4976), np.float32(0.775), np.float32(0.8459), np.float32(0.7218), np.float32(0.5742), np.float32(0.0), np.float32(0.0), np.float32(0.8231), np.float32(0.6422), np.float32(0.8382), np.float32(0.7093), np.float32(0.4073), np.float32(0.81), np.float32(0.9223), np.float32(0.9136), np.float32(0.6436), np.float32(0.6437), np.float32(0.4097), np.float32(0.8534), np.float32(0.5683), np.float32(0.7587), np.float32(0.0), np.float32(0.0), np.float32(0.5977), np.float32(0.6004), np.float32(0.955), np.float32(0.9685)] 
+2026-10-19 02:27:26.362331: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 02:27:26.667337: lr: 0.000785 
+2026-10-19 02:27:26.706866: saving checkpoint... 
+2026-10-19 02:27:26.842164: done, saving took 0.17 seconds 
+2026-10-19 02:27:26.843366: This epoch took 262.024078 s
+ 
+2026-10-19 02:27:26.843539: 
+epoch:  236 
+2026-10-19 02:32:01.781199: train loss : -0.7991 
+2026-10-19 02:32:07.123872: validation loss: -0.7204 
+2026-10-19 02:32:07.124718: Average global foreground Dice: [np.float32(0.9381), np.float32(0.7007), np.float32(0.8677), np.float32(0.8604), np.float32(0.8294), np.float32(0.9346), np.float32(0.879), np.float32(0.8297), np.float32(0.0), np.float32(0.4748), np.float32(0.7786), np.float32(0.8586), np.float32(0.7457), np.float32(0.6888), np.float32(0.0), np.float32(0.0), np.float32(0.8198), np.float32(0.6533), np.float32(0.8329), np.float32(0.6968), np.float32(0.2562), np.float32(0.7752), np.float32(0.9303), np.float32(0.9229), np.float32(0.6142), np.float32(0.6886), np.float32(0.3935), np.float32(0.9129), np.float32(0.5575), np.float32(0.7586), np.float32(0.0), np.float32(0.0), np.float32(0.5244), np.float32(0.5716), np.float32(0.9584), np.float32(0.9661)] 
+2026-10-19 02:32:07.124872: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 02:32:07.419469: lr: 0.000784 
+2026-10-19 02:32:07.427917: saving checkpoint... 
+2026-10-19 02:32:07.562207: done, saving took 0.14 seconds 
+2026-10-19 02:32:07.563354: This epoch took 280.719742 s
+ 
+2026-10-19 02:32:07.563534: 
+epoch:  237 
+2026-10-19 02:36:34.857579: train loss : -0.7913 
+2026-10-19 02:36:40.199079: validation loss: -0.7285 
+2026-10-19 02:36:40.200227: Average global foreground Dice: [np.float32(0.9378), np.float32(0.7016), np.float32(0.859), np.float32(0.8857), np.float32(0.8433), np.float32(0.9368), np.float32(0.8987), np.float32(0.61), np.float32(0.0), np.float32(0.4995), np.float32(0.7687), np.float32(0.8362), np.float32(0.7), np.float32(0.6149), np.float32(0.1233), np.float32(0.0), np.float32(0.8326), np.float32(0.6874), np.float32(0.8387), np.float32(0.7168), np.float32(0.2859), np.float32(0.7978), np.float32(0.8994), np.float32(0.8966), np.float32(0.6245), np.float32(0.6788), np.float32(0.4354), np.float32(0.8972), np.float32(0.6617), np.float32(0.7491), np.float32(0.0), np.float32(0.0), np.float32(0.5055), np.float32(0.6093), np.float32(0.9629), np.float32(0.9702)] 
+2026-10-19 02:36:40.200729: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 02:36:40.491552: lr: 0.000783 
+2026-10-19 02:36:40.499171: saving checkpoint... 
+2026-10-19 02:36:40.635182: done, saving took 0.14 seconds 
+2026-10-19 02:36:40.636680: This epoch took 273.073039 s
+ 
+2026-10-19 02:36:40.636894: 
+epoch:  238 
+2026-10-19 02:40:42.916989: train loss : -0.8101 
+2026-10-19 02:40:48.259418: validation loss: -0.7225 
+2026-10-19 02:40:48.260473: Average global foreground Dice: [np.float32(0.9455), np.float32(0.7355), np.float32(0.8743), np.float32(0.8881), np.float32(0.8458), np.float32(0.9398), np.float32(0.8919), np.float32(0.6888), np.float32(0.0), np.float32(0.5094), np.float32(0.7467), np.float32(0.8483), np.float32(0.7433), np.float32(0.6467), np.float32(0.0), np.float32(0.0), np.float32(0.8394), np.float32(0.6334), np.float32(0.8416), np.float32(0.7112), np.float32(0.3754), np.float32(0.7903), np.float32(0.9232), np.float32(0.9194), np.float32(0.6783), np.float32(0.6637), np.float32(0.3616), np.float32(0.6722), np.float32(0.6556), np.float32(0.8004), np.float32(0.0), np.float32(0.0), np.float32(0.6342), np.float32(0.6222), np.float32(0.9584), np.float32(0.9678)] 
+2026-10-19 02:40:48.260637: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 02:40:48.567992: lr: 0.000782 
+2026-10-19 02:40:48.575677: saving checkpoint... 
+2026-10-19 02:40:48.711617: done, saving took 0.14 seconds 
+2026-10-19 02:40:48.713053: This epoch took 248.076068 s
+ 
+2026-10-19 02:40:48.713260: 
+epoch:  239 
+2026-10-19 02:45:14.714339: train loss : -0.8047 
+2026-10-19 02:45:20.088403: validation loss: -0.7147 
+2026-10-19 02:45:20.089805: Average global foreground Dice: [np.float32(0.9421), np.float32(0.7059), np.float32(0.8634), np.float32(0.8907), np.float32(0.826), np.float32(0.9207), np.float32(0.8739), np.float32(0.5167), np.float32(0.0), np.float32(0.6173), np.float32(0.771), np.float32(0.8495), np.float32(0.7095), np.float32(0.5834), np.float32(0.0), np.float32(0.0), np.float32(0.8302), np.float32(0.6768), np.float32(0.8464), np.float32(0.7188), np.float32(0.3164), np.float32(0.7927), np.float32(0.918), np.float32(0.9185), np.float32(0.6553), np.float32(0.6909), np.float32(0.4225), np.float32(0.8622), np.float32(0.5876), np.float32(0.7627), np.float32(0.0), np.float32(0.0), np.float32(0.5734), np.float32(0.6021), np.float32(0.9557), np.float32(0.9633)] 
+2026-10-19 02:45:20.090682: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 02:45:20.385953: lr: 0.000781 
+2026-10-19 02:45:20.393718: saving checkpoint... 
+2026-10-19 02:45:20.720738: done, saving took 0.33 seconds 
+2026-10-19 02:45:20.722674: This epoch took 272.009319 s
+ 
+2026-10-19 02:45:20.723094: 
+epoch:  240 
+2026-10-19 02:49:55.130966: train loss : -0.7961 
+2026-10-19 02:50:00.485399: validation loss: -0.7111 
+2026-10-19 02:50:00.486651: Average global foreground Dice: [np.float32(0.9434), np.float32(0.7366), np.float32(0.8569), np.float32(0.8925), np.float32(0.8062), np.float32(0.9189), np.float32(0.8742), np.float32(0.6657), np.float32(0.0), np.float32(0.5818), np.float32(0.7677), np.float32(0.8308), np.float32(0.7339), np.float32(0.6282), np.float32(0.0), np.float32(0.0), np.float32(0.8226), np.float32(0.6723), np.float32(0.8394), np.float32(0.723), np.float32(0.3639), np.float32(0.7982), np.float32(0.9257), np.float32(0.9277), np.float32(0.6646), np.float32(0.6589), np.float32(0.3253), np.float32(0.7062), np.float32(0.6372), np.float32(0.7739), np.float32(0.0), np.float32(0.0), np.float32(0.6368), np.float32(0.5905), np.float32(0.9545), np.float32(0.9661)] 
+2026-10-19 02:50:00.486991: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 02:50:00.799436: lr: 0.00078 
+2026-10-19 02:50:00.808765: saving checkpoint... 
+2026-10-19 02:50:00.937330: done, saving took 0.14 seconds 
+2026-10-19 02:50:00.938927: This epoch took 280.215509 s
+ 
+2026-10-19 02:50:00.939188: 
+epoch:  241 
+2026-10-19 02:54:40.275243: train loss : -0.8027 
+2026-10-19 02:54:45.637762: validation loss: -0.7140 
+2026-10-19 02:54:45.639027: Average global foreground Dice: [np.float32(0.9235), np.float32(0.7222), np.float32(0.8627), np.float32(0.8735), np.float32(0.8068), np.float32(0.9231), np.float32(0.8955), np.float32(0.696), np.float32(0.0), np.float32(0.5573), np.float32(0.7506), np.float32(0.8342), np.float32(0.7202), np.float32(0.6346), np.float32(0.0152), np.float32(0.0), np.float32(0.8185), np.float32(0.6448), np.float32(0.8425), np.float32(0.7109), np.float32(0.3062), np.float32(0.7808), np.float32(0.931), np.float32(0.9143), np.float32(0.6507), np.float32(0.6687), np.float32(0.3501), np.float32(0.8263), np.float32(0.6084), np.float32(0.7204), np.float32(0.0), np.float32(0.0), np.float32(0.6105), np.float32(0.6074), np.float32(0.9539), np.float32(0.9596)] 
+2026-10-19 02:54:45.639417: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 02:54:45.947013: lr: 0.000779 
+2026-10-19 02:54:45.954978: saving checkpoint... 
+2026-10-19 02:54:46.094337: done, saving took 0.15 seconds 
+2026-10-19 02:54:46.095837: This epoch took 285.156554 s
+ 
+2026-10-19 02:54:46.095970: 
+epoch:  242 
+2026-10-19 02:59:00.341864: train loss : -0.8047 
+2026-10-19 02:59:05.716109: validation loss: -0.7248 
+2026-10-19 02:59:05.717106: Average global foreground Dice: [np.float32(0.9386), np.float32(0.7451), np.float32(0.8589), np.float32(0.8648), np.float32(0.8337), np.float32(0.924), np.float32(0.8972), np.float32(0.6769), np.float32(0.0), np.float32(0.5825), np.float32(0.7514), np.float32(0.8429), np.float32(0.7467), np.float32(0.6229), np.float32(0.0), np.float32(0.0), np.float32(0.8335), np.float32(0.6672), np.float32(0.8424), np.float32(0.7121), np.float32(0.3431), np.float32(0.7923), np.float32(0.9165), np.float32(0.9156), np.float32(0.6429), np.float32(0.6281), np.float32(0.3945), np.float32(0.8196), np.float32(0.672), np.float32(0.7911), np.float32(0.0), np.float32(0.0), np.float32(0.6086), np.float32(0.621), np.float32(0.9569), np.float32(0.9663)] 
+2026-10-19 02:59:05.717416: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 02:59:06.010119: lr: 0.000778 
+2026-10-19 02:59:06.018063: saving checkpoint... 
+2026-10-19 02:59:06.147669: done, saving took 0.14 seconds 
+2026-10-19 02:59:06.149002: This epoch took 260.052963 s
+ 
+2026-10-19 02:59:06.149237: 
+epoch:  243 
+2026-10-19 03:02:56.137041: train loss : -0.8073 
+2026-10-19 03:03:01.495532: validation loss: -0.7254 
+2026-10-19 03:03:01.496814: Average global foreground Dice: [np.float32(0.9344), np.float32(0.7401), np.float32(0.8611), np.float32(0.8479), np.float32(0.7854), np.float32(0.9361), np.float32(0.9007), np.float32(0.788), np.float32(0.0), np.float32(0.6095), np.float32(0.7539), np.float32(0.8539), np.float32(0.7113), np.float32(0.6463), np.float32(0.0083), np.float32(0.0), np.float32(0.838), np.float32(0.7005), np.float32(0.8511), np.float32(0.7532), np.float32(0.3248), np.float32(0.7969), np.float32(0.9282), np.float32(0.9129), np.float32(0.6671), np.float32(0.6932), np.float32(0.3848), np.float32(0.8647), np.float32(0.6471), np.float32(0.6481), np.float32(0.0), np.float32(0.0), np.float32(0.6804), np.float32(0.6122), np.float32(0.9564), np.float32(0.9656)] 
+2026-10-19 03:03:01.497113: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 03:03:01.826596: lr: 0.000777 
+2026-10-19 03:03:01.840173: saving checkpoint... 
+2026-10-19 03:03:01.975258: done, saving took 0.15 seconds 
+2026-10-19 03:03:01.976904: This epoch took 235.827555 s
+ 
+2026-10-19 03:03:01.977121: 
+epoch:  244 
+2026-10-19 03:07:22.685893: train loss : -0.8146 
+2026-10-19 03:07:28.039472: validation loss: -0.7277 
+2026-10-19 03:07:28.040476: Average global foreground Dice: [np.float32(0.9231), np.float32(0.7257), np.float32(0.8735), np.float32(0.8698), np.float32(0.7967), np.float32(0.923), np.float32(0.8866), np.float32(0.6534), np.float32(0.0), np.float32(0.6187), np.float32(0.7747), np.float32(0.8661), np.float32(0.7236), np.float32(0.6373), np.float32(0.0074), np.float32(0.0), np.float32(0.8155), np.float32(0.6198), np.float32(0.8315), np.float32(0.6566), np.float32(0.3023), np.float32(0.8059), np.float32(0.9065), np.float32(0.8875), np.float32(0.6121), np.float32(0.659), np.float32(0.3719), np.float32(0.8226), np.float32(0.6296), np.float32(0.7423), np.float32(0.0), np.float32(0.0), np.float32(0.6864), np.float32(0.6074), np.float32(0.9543), np.float32(0.9658)] 
+2026-10-19 03:07:28.040948: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 03:07:28.334514: lr: 0.000777 
+2026-10-19 03:07:28.343626: saving checkpoint... 
+2026-10-19 03:07:28.470968: done, saving took 0.14 seconds 
+2026-10-19 03:07:28.472935: This epoch took 266.495737 s
+ 
+2026-10-19 03:07:28.473107: 
+epoch:  245 
+2026-10-19 03:11:40.377935: train loss : -0.8058 
+2026-10-19 03:11:45.731890: validation loss: -0.7212 
+2026-10-19 03:11:45.733078: Average global foreground Dice: [np.float32(0.9449), np.float32(0.7811), np.float32(0.8793), np.float32(0.873), np.float32(0.8239), np.float32(0.9367), np.float32(0.8859), np.float32(0.7253), np.float32(0.0), np.float32(0.1821), np.float32(0.783), np.float32(0.834), np.float32(0.7375), np.float32(0.5823), np.float32(0.0029), np.float32(0.0), np.float32(0.8383), np.float32(0.6418), np.float32(0.8519), np.float32(0.7333), np.float32(0.388), np.float32(0.807), np.float32(0.9335), np.float32(0.9282), np.float32(0.6629), np.float32(0.7025), np.float32(0.3246), np.float32(0.7611), np.float32(0.6044), np.float32(0.7568), np.float32(0.0), np.float32(0.0), np.float32(0.693), np.float32(0.5988), np.float32(0.9552), np.float32(0.9683)] 
+2026-10-19 03:11:45.733573: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 03:11:46.029156: lr: 0.000776 
+2026-10-19 03:11:46.039632: saving checkpoint... 
+2026-10-19 03:11:46.169773: done, saving took 0.14 seconds 
+2026-10-19 03:11:46.171312: This epoch took 257.698111 s
+ 
+2026-10-19 03:11:46.171537: 
+epoch:  246 
+2026-10-19 03:15:50.104116: train loss : -0.8022 
+2026-10-19 03:15:55.466724: validation loss: -0.7269 
+2026-10-19 03:15:55.467681: Average global foreground Dice: [np.float32(0.9441), np.float32(0.7424), np.float32(0.854), np.float32(0.8542), np.float32(0.8204), np.float32(0.9398), np.float32(0.8965), np.float32(0.6095), np.float32(0.0), np.float32(0.3818), np.float32(0.7545), np.float32(0.8084), np.float32(0.7618), np.float32(0.6255), np.float32(0.0), np.float32(0.0), np.float32(0.8319), np.float32(0.647), np.float32(0.8433), np.float32(0.7093), np.float32(0.3566), np.float32(0.8358), np.float32(0.9138), np.float32(0.9096), np.float32(0.6509), np.float32(0.6841), np.float32(0.4183), np.float32(0.8831), np.float32(0.6547), np.float32(0.7601), np.float32(0.0), np.float32(0.0), np.float32(0.5914), np.float32(0.5922), np.float32(0.9538), np.float32(0.9678)] 
+2026-10-19 03:15:55.468140: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 03:15:55.752692: lr: 0.000775 
+2026-10-19 03:15:55.760218: saving checkpoint... 
+2026-10-19 03:15:55.887454: done, saving took 0.13 seconds 
+2026-10-19 03:15:55.888693: This epoch took 249.716970 s
+ 
+2026-10-19 03:15:55.888897: 
+epoch:  247 
+2026-10-19 03:20:26.861094: train loss : -0.8070 
+2026-10-19 03:20:32.217078: validation loss: -0.7205 
+2026-10-19 03:20:32.218375: Average global foreground Dice: [np.float32(0.9475), np.float32(0.7348), np.float32(0.8555), np.float32(0.8778), np.float32(0.821), np.float32(0.9338), np.float32(0.8848), np.float32(0.8308), np.float32(0.0), np.float32(0.3452), np.float32(0.7621), np.float32(0.819), np.float32(0.7275), np.float32(0.5668), np.float32(0.0027), np.float32(0.0), np.float32(0.8267), np.float32(0.6473), np.float32(0.836), np.float32(0.6884), np.float32(0.3289), np.float32(0.7343), np.float32(0.9215), np.float32(0.9278), np.float32(0.6172), np.float32(0.6601), np.float32(0.3988), np.float32(0.8416), np.float32(0.6107), np.float32(0.7375), np.float32(0.0), np.float32(0.0), np.float32(0.6505), np.float32(0.5481), np.float32(0.9595), np.float32(0.9668)] 
+2026-10-19 03:20:32.219041: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 03:20:32.507633: lr: 0.000774 
+2026-10-19 03:20:32.516497: saving checkpoint... 
+2026-10-19 03:20:32.648408: done, saving took 0.14 seconds 
+2026-10-19 03:20:32.649742: This epoch took 276.760765 s
+ 
+2026-10-19 03:20:32.649965: 
+epoch:  248 
+2026-10-19 03:24:38.963253: train loss : -0.8033 
+2026-10-19 03:24:44.314488: validation loss: -0.7133 
+2026-10-19 03:24:44.315638: Average global foreground Dice: [np.float32(0.9488), np.float32(0.731), np.float32(0.8856), np.float32(0.8784), np.float32(0.8076), np.float32(0.9311), np.float32(0.8865), np.float32(0.5906), np.float32(0.0), np.float32(0.4107), np.float32(0.7932), np.float32(0.8419), np.float32(0.7265), np.float32(0.5509), np.float32(0.0361), np.float32(0.0), np.float32(0.8337), np.float32(0.6673), np.float32(0.8491), np.float32(0.7143), np.float32(0.3087), np.float32(0.7744), np.float32(0.9288), np.float32(0.9317), np.float32(0.6749), np.float32(0.6976), np.float32(0.4338), np.float32(0.7877), np.float32(0.6282), np.float32(0.7852), np.float32(0.0), np.float32(0.0), np.float32(0.7035), np.float32(0.651), np.float32(0.9586), np.float32(0.9692)] 
+2026-10-19 03:24:44.316092: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 03:24:44.605685: lr: 0.000773 
+2026-10-19 03:24:44.613184: saving checkpoint... 
+2026-10-19 03:24:44.752358: done, saving took 0.15 seconds 
+2026-10-19 03:24:44.754163: This epoch took 252.104105 s
+ 
+2026-10-19 03:24:44.754353: 
+epoch:  249 
+2026-10-19 03:28:46.564543: train loss : -0.8089 
+2026-10-19 03:28:51.915410: validation loss: -0.7283 
+2026-10-19 03:28:51.916513: Average global foreground Dice: [np.float32(0.9438), np.float32(0.7416), np.float32(0.8586), np.float32(0.8639), np.float32(0.8164), np.float32(0.9294), np.float32(0.8873), np.float32(0.6839), np.float32(0.0), np.float32(0.3666), np.float32(0.7846), np.float32(0.8175), np.float32(0.7251), np.float32(0.6033), np.float32(0.0054), np.float32(0.0), np.float32(0.8341), np.float32(0.6866), np.float32(0.8507), np.float32(0.7397), np.float32(0.3235), np.float32(0.8233), np.float32(0.9349), np.float32(0.9238), np.float32(0.6711), np.float32(0.6986), np.float32(0.4221), np.float32(0.8849), np.float32(0.6126), np.float32(0.7359), np.float32(0.0), np.float32(0.0), np.float32(0.6838), np.float32(0.6363), np.float32(0.9617), np.float32(0.9682)] 
+2026-10-19 03:28:51.916712: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 03:28:52.199658: lr: 0.000772 
+2026-10-19 03:28:52.199910: saving scheduled checkpoint file... 
+2026-10-19 03:28:52.207854: saving checkpoint... 
+2026-10-19 03:28:52.336474: done, saving took 0.14 seconds 
+2026-10-19 03:28:52.338144: done 
+2026-10-19 03:28:52.345431: saving checkpoint... 
+2026-10-19 03:28:52.471970: done, saving took 0.13 seconds 
+2026-10-19 03:28:52.473444: This epoch took 247.718992 s
+ 
+2026-10-19 03:28:52.473603: 
+epoch:  250 
+2026-10-19 03:33:01.618034: train loss : -0.8082 
+2026-10-19 03:33:06.961797: validation loss: -0.7366 
+2026-10-19 03:33:06.962692: Average global foreground Dice: [np.float32(0.9422), np.float32(0.6982), np.float32(0.8764), np.float32(0.8726), np.float32(0.7671), np.float32(0.9402), np.float32(0.8821), np.float32(0.5388), np.float32(0.0), np.float32(0.5442), np.float32(0.7752), np.float32(0.8332), np.float32(0.6973), np.float32(0.6029), np.float32(0.0), np.float32(0.0), np.float32(0.8273), np.float32(0.6917), np.float32(0.8495), np.float32(0.7122), np.float32(0.2911), np.float32(0.7664), np.float32(0.9315), np.float32(0.9265), np.float32(0.6017), np.float32(0.6918), np.float32(0.4221), np.float32(0.8761), np.float32(0.5827), np.float32(0.7857), np.float32(0.0), np.float32(0.0), np.float32(0.6964), np.float32(0.6509), np.float32(0.9569), np.float32(0.9711)] 
+2026-10-19 03:33:06.963007: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 03:33:07.280052: lr: 0.000771 
+2026-10-19 03:33:07.288275: saving checkpoint... 
+2026-10-19 03:33:07.411530: done, saving took 0.13 seconds 
+2026-10-19 03:33:07.413547: This epoch took 254.939874 s
+ 
+2026-10-19 03:33:07.413725: 
+epoch:  251 
+2026-10-19 03:37:28.541418: train loss : -0.8141 
+2026-10-19 03:37:33.893134: validation loss: -0.7131 
+2026-10-19 03:37:33.894016: Average global foreground Dice: [np.float32(0.9436), np.float32(0.7107), np.float32(0.8683), np.float32(0.8809), np.float32(0.7959), np.float32(0.9381), np.float32(0.8801), np.float32(0.6675), np.float32(0.0), np.float32(0.517), np.float32(0.7571), np.float32(0.823), np.float32(0.6982), np.float32(0.6606), np.float32(0.0007), np.float32(0.0), np.float32(0.8289), np.float32(0.6769), np.float32(0.8451), np.float32(0.7223), np.float32(0.28), np.float32(0.8051), np.float32(0.9246), np.float32(0.919), np.float32(0.6409), np.float32(0.6243), np.float32(0.4119), np.float32(0.7188), np.float32(0.5654), np.float32(0.7668), np.float32(0.0), np.float32(0.0), np.float32(0.6162), np.float32(0.5951), np.float32(0.9603), np.float32(0.9699)] 
+2026-10-19 03:37:33.894165: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 03:37:34.182942: lr: 0.00077 
+2026-10-19 03:37:34.183218: This epoch took 266.769430 s
+ 
+2026-10-19 03:37:34.183312: 
+epoch:  252 
+2026-10-19 03:41:43.788040: train loss : -0.8147 
+2026-10-19 03:41:49.121124: validation loss: -0.7319 
+2026-10-19 03:41:49.122337: Average global foreground Dice: [np.float32(0.9298), np.float32(0.7155), np.float32(0.8722), np.float32(0.8601), np.float32(0.7991), np.float32(0.9321), np.float32(0.8818), np.float32(0.6769), np.float32(0.0), np.float32(0.4532), np.float32(0.7912), np.float32(0.8333), np.float32(0.7439), np.float32(0.6627), np.float32(0.0), np.float32(0.0), np.float32(0.8253), np.float32(0.6706), np.float32(0.8375), np.float32(0.7063), np.float32(0.2319), np.float32(0.7932), np.float32(0.9188), np.float32(0.9185), np.float32(0.6556), np.float32(0.6815), np.float32(0.4357), np.float32(0.8426), np.float32(0.5939), np.float32(0.7487), np.float32(0.0), np.float32(0.0), np.float32(0.7121), np.float32(0.6595), np.float32(0.9589), np.float32(0.9654)] 
+2026-10-19 03:41:49.122559: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 03:41:49.407449: lr: 0.000769 
+2026-10-19 03:41:49.414777: saving checkpoint... 
+2026-10-19 03:41:49.543427: done, saving took 0.14 seconds 
+2026-10-19 03:41:49.545026: This epoch took 255.361638 s
+ 
+2026-10-19 03:41:49.545266: 
+epoch:  253 
+2026-10-19 03:46:17.483123: train loss : -0.8152 
+2026-10-19 03:46:22.834054: validation loss: -0.7267 
+2026-10-19 03:46:22.835125: Average global foreground Dice: [np.float32(0.9347), np.float32(0.7544), np.float32(0.8719), np.float32(0.8539), np.float32(0.807), np.float32(0.9336), np.float32(0.8848), np.float32(0.7183), np.float32(0.0), np.float32(0.4416), np.float32(0.7485), np.float32(0.8048), np.float32(0.7438), np.float32(0.6391), np.float32(0.0303), np.float32(0.0), np.float32(0.8296), np.float32(0.6652), np.float32(0.8277), np.float32(0.7112), np.float32(0.4151), np.float32(0.8126), np.float32(0.9236), np.float32(0.9214), np.float32(0.6596), np.float32(0.6996), np.float32(0.3263), np.float32(0.7729), np.float32(0.6128), np.float32(0.7166), np.float32(0.0), np.float32(0.0), np.float32(0.6786), np.float32(0.6525), np.float32(0.9554), np.float32(0.967)] 
+2026-10-19 03:46:22.835330: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 03:46:23.116460: lr: 0.000768 
+2026-10-19 03:46:23.123869: saving checkpoint... 
+2026-10-19 03:46:23.253095: done, saving took 0.14 seconds 
+2026-10-19 03:46:23.254748: This epoch took 273.709385 s
+ 
+2026-10-19 03:46:23.254922: 
+epoch:  254 
+2026-10-19 03:50:13.390115: train loss : -0.8197 
+2026-10-19 03:50:18.737746: validation loss: -0.7024 
+2026-10-19 03:50:18.738799: Average global foreground Dice: [np.float32(0.9431), np.float32(0.7358), np.float32(0.8657), np.float32(0.8765), np.float32(0.8124), np.float32(0.9297), np.float32(0.8964), np.float32(0.7583), np.float32(0.0423), np.float32(0.4685), np.float32(0.7578), np.float32(0.8301), np.float32(0.7234), np.float32(0.6101), np.float32(0.0425), np.float32(0.0), np.float32(0.8262), np.float32(0.6628), np.float32(0.8416), np.float32(0.7142), np.float32(0.3097), np.float32(0.7986), np.float32(0.9221), np.float32(0.9201), np.float32(0.6572), np.float32(0.6975), np.float32(0.3982), np.float32(0.8218), np.float32(0.5693), np.float32(0.7445), np.float32(0.0), np.float32(0.0), np.float32(0.6411), np.float32(0.6301), np.float32(0.9556), np.float32(0.9694)] 
+2026-10-19 03:50:18.738987: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 03:50:19.029623: lr: 0.000767 
+2026-10-19 03:50:19.037066: saving checkpoint... 
+2026-10-19 03:50:19.165595: done, saving took 0.14 seconds 
+2026-10-19 03:50:19.166996: This epoch took 235.911980 s
+ 
+2026-10-19 03:50:19.167186: 
+epoch:  255 
+2026-10-19 03:54:56.156117: train loss : -0.8134 
+2026-10-19 03:55:01.521380: validation loss: -0.7406 
+2026-10-19 03:55:01.522613: Average global foreground Dice: [np.float32(0.9411), np.float32(0.7562), np.float32(0.8715), np.float32(0.8738), np.float32(0.8349), np.float32(0.9346), np.float32(0.8867), np.float32(0.7648), np.float32(0.0), np.float32(0.5262), np.float32(0.7571), np.float32(0.8346), np.float32(0.7631), np.float32(0.6537), np.float32(0.0151), np.float32(0.0), np.float32(0.8274), np.float32(0.6384), np.float32(0.8343), np.float32(0.7078), np.float32(0.2766), np.float32(0.7907), np.float32(0.9238), np.float32(0.927), np.float32(0.6039), np.float32(0.6541), np.float32(0.4232), np.float32(0.8665), np.float32(0.6397), np.float32(0.7418), np.float32(0.0), np.float32(0.0), np.float32(0.6254), np.float32(0.6267), np.float32(0.9538), np.float32(0.9671)] 
+2026-10-19 03:55:01.523155: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 03:55:01.821253: lr: 0.000766 
+2026-10-19 03:55:01.830951: saving checkpoint... 
+2026-10-19 03:55:01.967253: done, saving took 0.15 seconds 
+2026-10-19 03:55:01.968684: This epoch took 282.801423 s
+ 
+2026-10-19 03:55:01.968879: 
+epoch:  256 
+2026-10-19 03:59:24.557281: train loss : -0.8174 
+2026-10-19 03:59:29.915087: validation loss: -0.7380 
+2026-10-19 03:59:29.916014: Average global foreground Dice: [np.float32(0.9435), np.float32(0.7152), np.float32(0.8695), np.float32(0.8737), np.float32(0.813), np.float32(0.9412), np.float32(0.8832), np.float32(0.5854), np.float32(0.0), np.float32(0.5858), np.float32(0.785), np.float32(0.8391), np.float32(0.7227), np.float32(0.6128), np.float32(0.0), np.float32(0.0), np.float32(0.8336), np.float32(0.6778), np.float32(0.8468), np.float32(0.7355), np.float32(0.3551), np.float32(0.8195), np.float32(0.9253), np.float32(0.9339), np.float32(0.6051), np.float32(0.6901), np.float32(0.4379), np.float32(0.8452), np.float32(0.6476), np.float32(0.7298), np.float32(0.0), np.float32(0.0), np.float32(0.685), np.float32(0.6303), np.float32(0.9567), np.float32(0.9715)] 
+2026-10-19 03:59:29.916364: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 03:59:30.207447: lr: 0.000765 
+2026-10-19 03:59:30.216411: saving checkpoint... 
+2026-10-19 03:59:30.356274: done, saving took 0.15 seconds 
+2026-10-19 03:59:30.357718: This epoch took 268.388742 s
+ 
+2026-10-19 03:59:30.357899: 
+epoch:  257 
+2026-10-19 04:03:44.095172: train loss : -0.8177 
+2026-10-19 04:03:49.446593: validation loss: -0.7295 
+2026-10-19 04:03:49.447743: Average global foreground Dice: [np.float32(0.9455), np.float32(0.7637), np.float32(0.8729), np.float32(0.8524), np.float32(0.8348), np.float32(0.9382), np.float32(0.8909), np.float32(0.6225), np.float32(0.0), np.float32(0.4751), np.float32(0.7801), np.float32(0.838), np.float32(0.7215), np.float32(0.602), np.float32(0.03), np.float32(0.0), np.float32(0.8326), np.float32(0.6584), np.float32(0.8441), np.float32(0.7208), np.float32(0.3425), np.float32(0.7999), np.float32(0.9344), np.float32(0.9189), np.float32(0.6737), np.float32(0.6644), np.float32(0.411), np.float32(0.8355), np.float32(0.5745), np.float32(0.7462), np.float32(0.0), np.float32(0.0), np.float32(0.6383), np.float32(0.5716), np.float32(0.9547), np.float32(0.9716)] 
+2026-10-19 04:03:49.447994: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 04:03:49.737854: lr: 0.000764 
+2026-10-19 04:03:49.745409: saving checkpoint... 
+2026-10-19 04:03:49.878832: done, saving took 0.14 seconds 
+2026-10-19 04:03:49.880114: This epoch took 259.522131 s
+ 
+2026-10-19 04:03:49.880329: 
+epoch:  258 
+2026-10-19 04:08:16.615534: train loss : -0.8130 
+2026-10-19 04:08:21.964156: validation loss: -0.7297 
+2026-10-19 04:08:21.965126: Average global foreground Dice: [np.float32(0.9469), np.float32(0.7647), np.float32(0.8742), np.float32(0.8779), np.float32(0.8247), np.float32(0.9264), np.float32(0.8756), np.float32(0.6826), np.float32(0.0), np.float32(0.4601), np.float32(0.7799), np.float32(0.8583), np.float32(0.7112), np.float32(0.6251), np.float32(0.0257), np.float32(0.0), np.float32(0.8308), np.float32(0.6768), np.float32(0.8462), np.float32(0.7263), np.float32(0.3214), np.float32(0.7918), np.float32(0.9334), np.float32(0.9016), np.float32(0.6296), np.float32(0.6366), np.float32(0.4166), np.float32(0.8603), np.float32(0.6293), np.float32(0.7013), np.float32(0.0), np.float32(0.0), np.float32(0.6039), np.float32(0.6352), np.float32(0.9562), np.float32(0.9689)] 
+2026-10-19 04:08:21.965480: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 04:08:22.264698: lr: 0.000764 
+2026-10-19 04:08:22.275578: saving checkpoint... 
+2026-10-19 04:08:22.401386: done, saving took 0.14 seconds 
+2026-10-19 04:08:22.402958: This epoch took 272.522536 s
+ 
+2026-10-19 04:08:22.403253: 
+epoch:  259 
+2026-10-19 04:12:39.938321: train loss : -0.8181 
+2026-10-19 04:12:45.288297: validation loss: -0.7379 
+2026-10-19 04:12:45.289258: Average global foreground Dice: [np.float32(0.9445), np.float32(0.7456), np.float32(0.8773), np.float32(0.8715), np.float32(0.8307), np.float32(0.9317), np.float32(0.8841), np.float32(0.6535), np.float32(0.0), np.float32(0.5756), np.float32(0.7879), np.float32(0.8392), np.float32(0.7218), np.float32(0.6308), np.float32(0.0437), np.float32(0.0), np.float32(0.8257), np.float32(0.6537), np.float32(0.8344), np.float32(0.7135), np.float32(0.4114), np.float32(0.7569), np.float32(0.9288), np.float32(0.9167), np.float32(0.6278), np.float32(0.6732), np.float32(0.3604), np.float32(0.8824), np.float32(0.6159), np.float32(0.6982), np.float32(0.0), np.float32(0.0), np.float32(0.6858), np.float32(0.5911), np.float32(0.9531), np.float32(0.9688)] 
+2026-10-19 04:12:45.289433: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 04:12:45.624205: lr: 0.000763 
+2026-10-19 04:12:45.632334: saving checkpoint... 
+2026-10-19 04:12:45.763724: done, saving took 0.14 seconds 
+2026-10-19 04:12:45.765265: This epoch took 263.361763 s
+ 
+2026-10-19 04:12:45.765471: 
+epoch:  260 
+2026-10-19 04:17:06.757211: train loss : -0.8101 
+2026-10-19 04:17:12.126000: validation loss: -0.7514 
+2026-10-19 04:17:12.126976: Average global foreground Dice: [np.float32(0.947), np.float32(0.7727), np.float32(0.8829), np.float32(0.8968), np.float32(0.8476), np.float32(0.9294), np.float32(0.8891), np.float32(0.3264), np.float32(0.0), np.float32(0.599), np.float32(0.7818), np.float32(0.8346), np.float32(0.7684), np.float32(0.6227), np.float32(0.0041), np.float32(0.0), np.float32(0.8366), np.float32(0.6761), np.float32(0.8446), np.float32(0.7163), np.float32(0.3852), np.float32(0.8227), np.float32(0.9348), np.float32(0.9319), np.float32(0.6704), np.float32(0.6694), np.float32(0.306), np.float32(0.875), np.float32(0.6809), np.float32(0.7379), np.float32(0.0), np.float32(0.0), np.float32(0.6977), np.float32(0.6185), np.float32(0.9634), np.float32(0.9708)] 
+2026-10-19 04:17:12.127226: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 04:17:12.422730: lr: 0.000762 
+2026-10-19 04:17:12.430219: saving checkpoint... 
+2026-10-19 04:17:12.565499: done, saving took 0.14 seconds 
+2026-10-19 04:17:12.567430: This epoch took 266.801882 s
+ 
+2026-10-19 04:17:12.567637: 
+epoch:  261 
+2026-10-19 04:21:36.832883: train loss : -0.8154 
+2026-10-19 04:21:42.189354: validation loss: -0.7387 
+2026-10-19 04:21:42.190417: Average global foreground Dice: [np.float32(0.948), np.float32(0.7241), np.float32(0.8728), np.float32(0.8854), np.float32(0.802), np.float32(0.935), np.float32(0.8923), np.float32(0.5652), np.float32(0.0), np.float32(0.5872), np.float32(0.7937), np.float32(0.846), np.float32(0.7642), np.float32(0.6326), np.float32(0.182), np.float32(0.0), np.float32(0.8388), np.float32(0.6742), np.float32(0.8409), np.float32(0.7106), np.float32(0.2795), np.float32(0.7701), np.float32(0.9348), np.float32(0.9125), np.float32(0.6219), np.float32(0.6505), np.float32(0.3913), np.float32(0.8463), np.float32(0.621), np.float32(0.7603), np.float32(0.0), np.float32(0.0), np.float32(0.7298), np.float32(0.6028), np.float32(0.9657), np.float32(0.9709)] 
+2026-10-19 04:21:42.190683: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 04:21:42.477161: lr: 0.000761 
+2026-10-19 04:21:42.485778: saving checkpoint... 
+2026-10-19 04:21:42.618357: done, saving took 0.14 seconds 
+2026-10-19 04:21:42.619477: This epoch took 270.051750 s
+ 
+2026-10-19 04:21:42.619629: 
+epoch:  262 
+2026-10-19 04:25:48.062187: train loss : -0.8205 
+2026-10-19 04:25:53.434462: validation loss: -0.7280 
+2026-10-19 04:25:53.435652: Average global foreground Dice: [np.float32(0.944), np.float32(0.7394), np.float32(0.8785), np.float32(0.8898), np.float32(0.8063), np.float32(0.9288), np.float32(0.8876), np.float32(0.5226), np.float32(0.0), np.float32(0.4044), np.float32(0.7576), np.float32(0.8229), np.float32(0.7553), np.float32(0.5657), np.float32(0.0326), np.float32(0.0), np.float32(0.8383), np.float32(0.6795), np.float32(0.846), np.float32(0.7486), np.float32(0.3916), np.float32(0.787), np.float32(0.9408), np.float32(0.9304), np.float32(0.6503), np.float32(0.6556), np.float32(0.3694), np.float32(0.8389), np.float32(0.6296), np.float32(0.7759), np.float32(0.0), np.float32(0.0), np.float32(0.6404), np.float32(0.5726), np.float32(0.9659), np.float32(0.9682)] 
+2026-10-19 04:25:53.435961: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 04:25:53.757777: lr: 0.00076 
+2026-10-19 04:25:53.758093: This epoch took 251.138391 s
+ 
+2026-10-19 04:25:53.758241: 
+epoch:  263 
+2026-10-19 04:30:21.806273: train loss : -0.8231 
+2026-10-19 04:30:27.153259: validation loss: -0.7206 
+2026-10-19 04:30:27.154344: Average global foreground Dice: [np.float32(0.9461), np.float32(0.6703), np.float32(0.8773), np.float32(0.8798), np.float32(0.7743), np.float32(0.9371), np.float32(0.8782), np.float32(0.6626), np.float32(0.0), np.float32(0.5259), np.float32(0.7551), np.float32(0.8303), np.float32(0.7192), np.float32(0.6074), np.float32(0.0), np.float32(0.0), np.float32(0.8117), np.float32(0.636), np.float32(0.8309), np.float32(0.7176), np.float32(0.3204), np.float32(0.7801), np.float32(0.9268), np.float32(0.9178), np.float32(0.6209), np.float32(0.6694), np.float32(0.4063), np.float32(0.8872), np.float32(0.5075), np.float32(0.7761), np.float32(0.0), np.float32(0.0), np.float32(0.7227), np.float32(0.6475), np.float32(0.9565), np.float32(0.9685)] 
+2026-10-19 04:30:27.154672: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 04:30:27.444825: lr: 0.000759 
+2026-10-19 04:30:27.445334: This epoch took 273.686927 s
+ 
+2026-10-19 04:30:27.445521: 
+epoch:  264 
+2026-10-19 04:34:29.606670: train loss : -0.8162 
+2026-10-19 04:34:34.970600: validation loss: -0.7316 
+2026-10-19 04:34:34.973643: Average global foreground Dice: [np.float32(0.9375), np.float32(0.7058), np.float32(0.8661), np.float32(0.8543), np.float32(0.7953), np.float32(0.9308), np.float32(0.8906), np.float32(0.5901), np.float32(0.0), np.float32(0.4999), np.float32(0.7857), np.float32(0.8228), np.float32(0.739), np.float32(0.591), np.float32(0.0), np.float32(0.0), np.float32(0.8318), np.float32(0.6877), np.float32(0.846), np.float32(0.7224), np.float32(0.3337), np.float32(0.7525), np.float32(0.9274), np.float32(0.9183), np.float32(0.6235), np.float32(0.658), np.float32(0.3783), np.float32(0.8627), np.float32(0.5759), np.float32(0.7719), np.float32(0.0), np.float32(0.0), np.float32(0.7126), np.float32(0.6438), np.float32(0.9602), np.float32(0.9695)] 
+2026-10-19 04:34:34.974190: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 04:34:35.253131: lr: 0.000758 
+2026-10-19 04:34:35.253537: This epoch took 247.807906 s
+ 
+2026-10-19 04:34:35.253799: 
+epoch:  265 
+2026-10-19 04:38:53.374355: train loss : -0.7875 
+2026-10-19 04:38:58.715214: validation loss: -0.7163 
+2026-10-19 04:38:58.716255: Average global foreground Dice: [np.float32(0.9348), np.float32(0.7788), np.float32(0.8576), np.float32(0.8812), np.float32(0.828), np.float32(0.9357), np.float32(0.8848), np.float32(0.8053), np.float32(0.0), np.float32(0.6082), np.float32(0.7659), np.float32(0.8018), np.float32(0.7448), np.float32(0.6478), np.float32(0.0063), np.float32(0.0), np.float32(0.8358), np.float32(0.6195), np.float32(0.8439), np.float32(0.6902), np.float32(0.3657), np.float32(0.7777), np.float32(0.8478), np.float32(0.8765), np.float32(0.6376), np.float32(0.6382), np.float32(0.4336), np.float32(0.8454), np.float32(0.608), np.float32(0.757), np.float32(0.0), np.float32(0.0), np.float32(0.7076), np.float32(0.6598), np.float32(0.9476), np.float32(0.9666)] 
+2026-10-19 04:38:58.716788: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 04:38:59.005570: lr: 0.000757 
+2026-10-19 04:38:59.005829: This epoch took 263.751801 s
+ 
+2026-10-19 04:38:59.006018: 
+epoch:  266 
+2026-10-19 04:43:34.606383: train loss : -0.8012 
+2026-10-19 04:43:39.960963: validation loss: -0.7312 
+2026-10-19 04:43:39.962596: Average global foreground Dice: [np.float32(0.9397), np.float32(0.7432), np.float32(0.8564), np.float32(0.876), np.float32(0.8332), np.float32(0.9393), np.float32(0.8883), np.float32(0.7662), np.float32(0.0), np.float32(0.4591), np.float32(0.7763), np.float32(0.8238), np.float32(0.7367), np.float32(0.6464), np.float32(0.0), np.float32(0.0), np.float32(0.8203), np.float32(0.6601), np.float32(0.8261), np.float32(0.6996), np.float32(0.3228), np.float32(0.7507), np.float32(0.9309), np.float32(0.9192), np.float32(0.6272), np.float32(0.6537), np.float32(0.3529), np.float32(0.8621), np.float32(0.5547), np.float32(0.796), np.float32(0.0), np.float32(0.0), np.float32(0.6976), np.float32(0.6175), np.float32(0.9546), np.float32(0.97)] 
+2026-10-19 04:43:39.962955: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 04:43:40.288507: lr: 0.000756 
+2026-10-19 04:43:40.296084: saving checkpoint... 
+2026-10-19 04:43:40.438758: done, saving took 0.15 seconds 
+2026-10-19 04:43:40.440340: This epoch took 281.434220 s
+ 
+2026-10-19 04:43:40.440534: 
+epoch:  267 
+2026-10-19 04:48:04.345121: train loss : -0.8038 
+2026-10-19 04:48:09.694632: validation loss: -0.7252 
+2026-10-19 04:48:09.695739: Average global foreground Dice: [np.float32(0.931), np.float32(0.7186), np.float32(0.8587), np.float32(0.8953), np.float32(0.8202), np.float32(0.9345), np.float32(0.8847), np.float32(0.7059), np.float32(0.0), np.float32(0.5401), np.float32(0.7713), np.float32(0.8154), np.float32(0.7126), np.float32(0.6013), np.float32(0.0), np.float32(0.0), np.float32(0.823), np.float32(0.6266), np.float32(0.8215), np.float32(0.6652), np.float32(0.2691), np.float32(0.7502), np.float32(0.9318), np.float32(0.898), np.float32(0.5687), np.float32(0.6251), np.float32(0.348), np.float32(0.8528), np.float32(0.5939), np.float32(0.745), np.float32(0.0), np.float32(0.0), np.float32(0.7447), np.float32(0.612), np.float32(0.9609), np.float32(0.9672)] 
+2026-10-19 04:48:09.696282: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 04:48:10.003551: lr: 0.000755 
+2026-10-19 04:48:10.003846: This epoch took 269.563233 s
+ 
+2026-10-19 04:48:10.004056: 
+epoch:  268 
+2026-10-19 04:52:57.520271: train loss : -0.8012 
+2026-10-19 04:53:02.894189: validation loss: -0.7398 
+2026-10-19 04:53:02.895256: Average global foreground Dice: [np.float32(0.9374), np.float32(0.7587), np.float32(0.8626), np.float32(0.8924), np.float32(0.8281), np.float32(0.9386), np.float32(0.8749), np.float32(0.7624), np.float32(0.0), np.float32(0.583), np.float32(0.7733), np.float32(0.8623), np.float32(0.7525), np.float32(0.6079), np.float32(0.0233), np.float32(0.0), np.float32(0.8306), np.float32(0.6607), np.float32(0.8383), np.float32(0.7172), np.float32(0.3849), np.float32(0.7526), np.float32(0.9257), np.float32(0.9196), np.float32(0.6998), np.float32(0.6285), np.float32(0.424), np.float32(0.7907), np.float32(0.608), np.float32(0.7365), np.float32(0.0), np.float32(0.0), np.float32(0.7616), np.float32(0.6272), np.float32(0.9519), np.float32(0.9687)] 
+2026-10-19 04:53:02.895475: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 04:53:03.200541: lr: 0.000754 
+2026-10-19 04:53:03.209639: saving checkpoint... 
+2026-10-19 04:53:03.350202: done, saving took 0.15 seconds 
+2026-10-19 04:53:03.352114: This epoch took 293.347807 s
+ 
+2026-10-19 04:53:03.352437: 
+epoch:  269 
+2026-10-19 04:57:18.650781: train loss : -0.8122 
+2026-10-19 04:57:24.031757: validation loss: -0.7289 
+2026-10-19 04:57:24.032722: Average global foreground Dice: [np.float32(0.9417), np.float32(0.7363), np.float32(0.8641), np.float32(0.892), np.float32(0.8078), np.float32(0.9354), np.float32(0.8994), np.float32(0.8254), np.float32(0.0), np.float32(0.514), np.float32(0.7698), np.float32(0.8537), np.float32(0.752), np.float32(0.6428), np.float32(0.0), np.float32(0.0), np.float32(0.8262), np.float32(0.6789), np.float32(0.8427), np.float32(0.7187), np.float32(0.3363), np.float32(0.7346), np.float32(0.8327), np.float32(0.8402), np.float32(0.608), np.float32(0.6295), np.float32(0.3813), np.float32(0.8157), np.float32(0.5963), np.float32(0.7228), np.float32(0.0), np.float32(0.0), np.float32(0.7159), np.float32(0.634), np.float32(0.957), np.float32(0.9677)] 
+2026-10-19 04:57:24.032913: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 04:57:24.353463: lr: 0.000753 
+2026-10-19 04:57:24.353753: This epoch took 261.001145 s
+ 
+2026-10-19 04:57:24.353862: 
+epoch:  270 
+2026-10-19 05:01:56.296293: train loss : -0.8165 
+2026-10-19 05:02:01.645251: validation loss: -0.7551 
+2026-10-19 05:02:01.646488: Average global foreground Dice: [np.float32(0.9438), np.float32(0.7894), np.float32(0.8766), np.float32(0.8958), np.float32(0.8335), np.float32(0.9372), np.float32(0.8944), np.float32(0.8275), np.float32(0.0), np.float32(0.6405), np.float32(0.8159), np.float32(0.8705), np.float32(0.7694), np.float32(0.6637), np.float32(0.0553), np.float32(0.0), np.float32(0.8312), np.float32(0.6812), np.float32(0.8422), np.float32(0.7126), np.float32(0.3577), np.float32(0.7926), np.float32(0.9371), np.float32(0.9235), np.float32(0.6997), np.float32(0.6745), np.float32(0.4188), np.float32(0.8252), np.float32(0.7032), np.float32(0.8028), np.float32(0.0), np.float32(0.0), np.float32(0.7398), np.float32(0.6282), np.float32(0.9613), np.float32(0.9656)] 
+2026-10-19 05:02:01.646707: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 05:02:01.943443: lr: 0.000752 
+2026-10-19 05:02:01.951747: saving checkpoint... 
+2026-10-19 05:02:02.075167: done, saving took 0.13 seconds 
+2026-10-19 05:02:02.077013: This epoch took 277.723076 s
+ 
+2026-10-19 05:02:02.077184: 
+epoch:  271 
+2026-10-19 05:06:35.046501: train loss : -0.8088 
+2026-10-19 05:06:40.396287: validation loss: -0.7283 
+2026-10-19 05:06:40.397284: Average global foreground Dice: [np.float32(0.9448), np.float32(0.7438), np.float32(0.8815), np.float32(0.8985), np.float32(0.8036), np.float32(0.9283), np.float32(0.894), np.float32(0.7987), np.float32(0.0), np.float32(0.4484), np.float32(0.7601), np.float32(0.8127), np.float32(0.7171), np.float32(0.6058), np.float32(0.0), np.float32(0.0), np.float32(0.8298), np.float32(0.6761), np.float32(0.8473), np.float32(0.7255), np.float32(0.4143), np.float32(0.7878), np.float32(0.9271), np.float32(0.924), np.float32(0.6693), np.float32(0.6817), np.float32(0.4263), np.float32(0.8519), np.float32(0.6063), np.float32(0.7336), np.float32(0.0), np.float32(0.0), np.float32(0.6895), np.float32(0.6322), np.float32(0.9547), np.float32(0.9686)] 
+2026-10-19 05:06:40.397564: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 05:06:40.690779: lr: 0.000751 
+2026-10-19 05:06:40.699928: saving checkpoint... 
+2026-10-19 05:06:40.837924: done, saving took 0.15 seconds 
+2026-10-19 05:06:40.839626: This epoch took 278.762357 s
+ 
+2026-10-19 05:06:40.839829: 
+epoch:  272 
+2026-10-19 05:10:46.963697: train loss : -0.8157 
+2026-10-19 05:10:52.344238: validation loss: -0.7099 
+2026-10-19 05:10:52.345412: Average global foreground Dice: [np.float32(0.9441), np.float32(0.7389), np.float32(0.8495), np.float32(0.8927), np.float32(0.8164), np.float32(0.9282), np.float32(0.8847), np.float32(0.8097), np.float32(0.0), np.float32(0.5576), np.float32(0.7715), np.float32(0.8434), np.float32(0.662), np.float32(0.5344), np.float32(0.0), np.float32(0.0256), np.float32(0.8319), np.float32(0.6652), np.float32(0.8479), np.float32(0.7399), np.float32(0.4968), np.float32(0.7675), np.float32(0.9367), np.float32(0.9292), np.float32(0.6723), np.float32(0.6507), np.float32(0.3177), np.float32(0.8339), np.float32(0.582), np.float32(0.6947), np.float32(0.0), np.float32(0.0), np.float32(0.708), np.float32(0.6625), np.float32(0.953), np.float32(0.9683)] 
+2026-10-19 05:10:52.345819: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 05:10:52.641988: lr: 0.000751 
+2026-10-19 05:10:52.650019: saving checkpoint... 
+2026-10-19 05:10:52.781384: done, saving took 0.14 seconds 
+2026-10-19 05:10:52.782854: This epoch took 251.942935 s
+ 
+2026-10-19 05:10:52.782964: 
+epoch:  273 
+2026-10-19 05:15:02.095263: train loss : -0.8194 
+2026-10-19 05:15:07.453325: validation loss: -0.7333 
+2026-10-19 05:15:07.454454: Average global foreground Dice: [np.float32(0.942), np.float32(0.7256), np.float32(0.8732), np.float32(0.8935), np.float32(0.8177), np.float32(0.9324), np.float32(0.8751), np.float32(0.8133), np.float32(0.0), np.float32(0.5459), np.float32(0.7709), np.float32(0.8354), np.float32(0.7359), np.float32(0.5685), np.float32(0.0), np.float32(0.0), np.float32(0.8253), np.float32(0.6611), np.float32(0.8377), np.float32(0.6916), np.float32(0.3932), np.float32(0.7702), np.float32(0.9143), np.float32(0.9185), np.float32(0.6609), np.float32(0.6716), np.float32(0.3843), np.float32(0.8408), np.float32(0.5782), np.float32(0.711), np.float32(0.0), np.float32(0.0), np.float32(0.7512), np.float32(0.661), np.float32(0.9565), np.float32(0.9662)] 
+2026-10-19 05:15:07.454720: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 05:15:07.765484: lr: 0.00075 
+2026-10-19 05:15:07.775603: saving checkpoint... 
+2026-10-19 05:15:07.902070: done, saving took 0.14 seconds 
+2026-10-19 05:15:07.903849: This epoch took 255.120831 s
+ 
+2026-10-19 05:15:07.904034: 
+epoch:  274 
+2026-10-19 05:19:55.049918: train loss : -0.8159 
+2026-10-19 05:20:00.414962: validation loss: -0.7375 
+2026-10-19 05:20:00.415992: Average global foreground Dice: [np.float32(0.9461), np.float32(0.7593), np.float32(0.8691), np.float32(0.9042), np.float32(0.8447), np.float32(0.9415), np.float32(0.8946), np.float32(0.8061), np.float32(0.0), np.float32(0.5275), np.float32(0.7711), np.float32(0.8421), np.float32(0.7516), np.float32(0.6036), np.float32(0.0), np.float32(0.0), np.float32(0.835), np.float32(0.6659), np.float32(0.8408), np.float32(0.714), np.float32(0.3711), np.float32(0.7714), np.float32(0.9201), np.float32(0.9088), np.float32(0.6922), np.float32(0.6534), np.float32(0.381), np.float32(0.8122), np.float32(0.6452), np.float32(0.729), np.float32(0.0), np.float32(0.0), np.float32(0.7243), np.float32(0.6267), np.float32(0.95), np.float32(0.969)] 
+2026-10-19 05:20:00.416173: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 05:20:00.706424: lr: 0.000749 
+2026-10-19 05:20:00.714157: saving checkpoint... 
+2026-10-19 05:20:00.844433: done, saving took 0.14 seconds 
+2026-10-19 05:20:00.845626: This epoch took 292.941503 s
+ 
+2026-10-19 05:20:00.845819: 
+epoch:  275 
+2026-10-19 05:24:06.138919: train loss : -0.8196 
+2026-10-19 05:24:11.506951: validation loss: -0.7151 
+2026-10-19 05:24:11.507951: Average global foreground Dice: [np.float32(0.9435), np.float32(0.7296), np.float32(0.8609), np.float32(0.8757), np.float32(0.8074), np.float32(0.9352), np.float32(0.887), np.float32(0.6555), np.float32(0.0), np.float32(0.5209), np.float32(0.7456), np.float32(0.8223), np.float32(0.7348), np.float32(0.632), np.float32(0.0008), np.float32(0.0), np.float32(0.8174), np.float32(0.6292), np.float32(0.836), np.float32(0.7013), np.float32(0.3113), np.float32(0.7684), np.float32(0.9227), np.float32(0.921), np.float32(0.6137), np.float32(0.6835), np.float32(0.3513), np.float32(0.8385), np.float32(0.6014), np.float32(0.6965), np.float32(0.0), np.float32(0.0), np.float32(0.7332), np.float32(0.6265), np.float32(0.9489), np.float32(0.9687)] 
+2026-10-19 05:24:11.508101: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 05:24:11.804317: lr: 0.000748 
+2026-10-19 05:24:11.804578: This epoch took 250.958682 s
+ 
+2026-10-19 05:24:11.804795: 
+epoch:  276 
+2026-10-19 05:28:45.577226: train loss : -0.8179 
+2026-10-19 05:28:50.927152: validation loss: -0.7344 
+2026-10-19 05:28:50.928289: Average global foreground Dice: [np.float32(0.9454), np.float32(0.7349), np.float32(0.8741), np.float32(0.8952), np.float32(0.8398), np.float32(0.9401), np.float32(0.8874), np.float32(0.6282), np.float32(0.0), np.float32(0.5878), np.float32(0.7818), np.float32(0.8575), np.float32(0.7343), np.float32(0.6356), np.float32(0.0), np.float32(0.0), np.float32(0.8382), np.float32(0.6676), np.float32(0.8369), np.float32(0.7091), np.float32(0.3357), np.float32(0.7819), np.float32(0.9289), np.float32(0.9281), np.float32(0.6531), np.float32(0.6966), np.float32(0.4554), np.float32(0.8489), np.float32(0.5912), np.float32(0.716), np.float32(0.0), np.float32(0.0), np.float32(0.7366), np.float32(0.6435), np.float32(0.9542), np.float32(0.9691)] 
+2026-10-19 05:28:50.928448: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 05:28:51.217493: lr: 0.000747 
+2026-10-19 05:28:51.217979: This epoch took 279.412971 s
+ 
+2026-10-19 05:28:51.218307: 
+epoch:  277 
+2026-10-19 05:33:10.381583: train loss : -0.8090 
+2026-10-19 05:33:15.750312: validation loss: -0.7324 
+2026-10-19 05:33:15.751398: Average global foreground Dice: [np.float32(0.9427), np.float32(0.7636), np.float32(0.8712), np.float32(0.8796), np.float32(0.8204), np.float32(0.945), np.float32(0.8878), np.float32(0.7937), np.float32(0.0), np.float32(0.543), np.float32(0.7665), np.float32(0.8314), np.float32(0.7316), np.float32(0.617), np.float32(0.0421), np.float32(0.0), np.float32(0.8333), np.float32(0.6371), np.float32(0.846), np.float32(0.725), np.float32(0.3373), np.float32(0.7745), np.float32(0.9103), np.float32(0.9104), np.float32(0.6642), np.float32(0.6971), np.float32(0.3789), np.float32(0.8491), np.float32(0.6269), np.float32(0.7347), np.float32(0.0), np.float32(0.0), np.float32(0.7304), np.float32(0.6524), np.float32(0.9509), np.float32(0.9694)] 
+2026-10-19 05:33:15.751762: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 05:33:16.047087: lr: 0.000746 
+2026-10-19 05:33:16.054588: saving checkpoint... 
+2026-10-19 05:33:16.183635: done, saving took 0.14 seconds 
+2026-10-19 05:33:16.185412: This epoch took 264.966864 s
+ 
+2026-10-19 05:33:16.185605: 
+epoch:  278 
+2026-10-19 05:37:30.970602: train loss : -0.8123 
+2026-10-19 05:37:36.330152: validation loss: -0.7320 
+2026-10-19 05:37:36.331141: Average global foreground Dice: [np.float32(0.945), np.float32(0.7226), np.float32(0.8748), np.float32(0.877), np.float32(0.7635), np.float32(0.9392), np.float32(0.8782), np.float32(0.7543), np.float32(0.0), np.float32(0.5908), np.float32(0.778), np.float32(0.8515), np.float32(0.7136), np.float32(0.6352), np.float32(0.0376), np.float32(0.0), np.float32(0.8258), np.float32(0.6771), np.float32(0.8369), np.float32(0.6989), np.float32(0.3004), np.float32(0.7754), np.float32(0.9341), np.float32(0.9286), np.float32(0.6123), np.float32(0.6541), np.float32(0.3331), np.float32(0.7845), np.float32(0.6442), np.float32(0.7539), np.float32(0.0), np.float32(0.0), np.float32(0.7465), np.float32(0.6077), np.float32(0.9541), np.float32(0.9675)] 
+2026-10-19 05:37:36.331404: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 05:37:36.628245: lr: 0.000745 
+2026-10-19 05:37:36.628572: This epoch took 260.442805 s
+ 
+2026-10-19 05:37:36.628861: 
+epoch:  279 
+2026-10-19 05:42:00.189692: train loss : -0.8206 
+2026-10-19 05:42:05.573020: validation loss: -0.7355 
+2026-10-19 05:42:05.574117: Average global foreground Dice: [np.float32(0.9472), np.float32(0.7313), np.float32(0.8707), np.float32(0.889), np.float32(0.8139), np.float32(0.9381), np.float32(0.8758), np.float32(0.8465), np.float32(0.0), np.float32(0.6367), np.float32(0.7787), np.float32(0.848), np.float32(0.692), np.float32(0.6005), np.float32(0.0), np.float32(0.0), np.float32(0.8166), np.float32(0.681), np.float32(0.8486), np.float32(0.6989), np.float32(0.2689), np.float32(0.7848), np.float32(0.9308), np.float32(0.9393), np.float32(0.6445), np.float32(0.6521), np.float32(0.3191), np.float32(0.8535), np.float32(0.5776), np.float32(0.7646), np.float32(0.0), np.float32(0.0), np.float32(0.7327), np.float32(0.639), np.float32(0.9596), np.float32(0.9693)] 
+2026-10-19 05:42:05.574576: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 05:42:05.914675: lr: 0.000744 
+2026-10-19 05:42:05.922485: saving checkpoint... 
+2026-10-19 05:42:06.053588: done, saving took 0.14 seconds 
+2026-10-19 05:42:06.054940: This epoch took 269.425956 s
+ 
+2026-10-19 05:42:06.055069: 
+epoch:  280 
+2026-10-19 05:46:27.737693: train loss : -0.8182 
+2026-10-19 05:46:33.084502: validation loss: -0.7214 
+2026-10-19 05:46:33.085524: Average global foreground Dice: [np.float32(0.9204), np.float32(0.7271), np.float32(0.8804), np.float32(0.8835), np.float32(0.8006), np.float32(0.9378), np.float32(0.8826), np.float32(0.7214), np.float32(0.0), np.float32(0.6092), np.float32(0.7743), np.float32(0.8536), np.float32(0.7373), np.float32(0.6107), np.float32(0.0), np.float32(0.0), np.float32(0.8159), np.float32(0.6598), np.float32(0.8383), np.float32(0.7007), np.float32(0.3219), np.float32(0.7639), np.float32(0.9061), np.float32(0.9015), np.float32(0.6297), np.float32(0.7052), np.float32(0.3629), np.float32(0.8538), np.float32(0.6049), np.float32(0.7537), np.float32(0.0), np.float32(0.0), np.float32(0.6999), np.float32(0.6037), np.float32(0.9563), np.float32(0.9698)] 
+2026-10-19 05:46:33.085716: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 05:46:33.387082: lr: 0.000743 
+2026-10-19 05:46:33.387367: This epoch took 267.332223 s
+ 
+2026-10-19 05:46:33.387467: 
+epoch:  281 
+2026-10-19 05:50:37.949628: train loss : -0.8176 
+2026-10-19 05:50:43.302358: validation loss: -0.7321 
+2026-10-19 05:50:43.303396: Average global foreground Dice: [np.float32(0.9458), np.float32(0.7226), np.float32(0.8749), np.float32(0.8986), np.float32(0.8179), np.float32(0.9304), np.float32(0.8921), np.float32(0.6401), np.float32(0.0), np.float32(0.4151), np.float32(0.7676), np.float32(0.8588), np.float32(0.7149), np.float32(0.5873), np.float32(0.0), np.float32(0.0), np.float32(0.8258), np.float32(0.6871), np.float32(0.8511), np.float32(0.7273), np.float32(0.3013), np.float32(0.7621), np.float32(0.9296), np.float32(0.931), np.float32(0.6154), np.float32(0.6856), np.float32(0.2991), np.float32(0.8417), np.float32(0.6447), np.float32(0.7564), np.float32(0.0), np.float32(0.0), np.float32(0.7115), np.float32(0.6742), np.float32(0.9587), np.float32(0.9689)] 
+2026-10-19 05:50:43.303654: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 05:50:43.592243: lr: 0.000742 
+2026-10-19 05:50:43.592639: This epoch took 250.204910 s
+ 
+2026-10-19 05:50:43.592863: 
+epoch:  282 
+2026-10-19 05:54:51.487614: train loss : -0.8208 
+2026-10-19 05:54:56.855628: validation loss: -0.7364 
+2026-10-19 05:54:56.856670: Average global foreground Dice: [np.float32(0.941), np.float32(0.7442), np.float32(0.8572), np.float32(0.8894), np.float32(0.8334), np.float32(0.9329), np.float32(0.8824), np.float32(0.6822), np.float32(0.0), np.float32(0.4874), np.float32(0.7589), np.float32(0.8412), np.float32(0.7284), np.float32(0.5843), np.float32(0.0), np.float32(0.0), np.float32(0.8249), np.float32(0.6619), np.float32(0.8369), np.float32(0.7201), np.float32(0.3602), np.float32(0.7841), np.float32(0.9127), np.float32(0.9144), np.float32(0.657), np.float32(0.6551), np.float32(0.4687), np.float32(0.7806), np.float32(0.6344), np.float32(0.6894), np.float32(0.0), np.float32(0.0), np.float32(0.6856), np.float32(0.6094), np.float32(0.9521), np.float32(0.964)] 
+2026-10-19 05:54:56.857013: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 05:54:57.143781: lr: 0.000741 
+2026-10-19 05:54:57.144247: This epoch took 253.551211 s
+ 
+2026-10-19 05:54:57.144573: 
+epoch:  283 
+2026-10-19 05:58:55.162722: train loss : -0.8242 
+2026-10-19 05:59:00.518333: validation loss: -0.7359 
+2026-10-19 05:59:00.519586: Average global foreground Dice: [np.float32(0.9443), np.float32(0.7527), np.float32(0.8607), np.float32(0.8835), np.float32(0.8144), np.float32(0.9369), np.float32(0.8969), np.float32(0.8166), np.float32(0.0), np.float32(0.4626), np.float32(0.7441), np.float32(0.8319), np.float32(0.7307), np.float32(0.6289), np.float32(0.0), np.float32(0.0), np.float32(0.8223), np.float32(0.5813), np.float32(0.8263), np.float32(0.6865), np.float32(0.3265), np.float32(0.7671), np.float32(0.9225), np.float32(0.9229), np.float32(0.6226), np.float32(0.6904), np.float32(0.4024), np.float32(0.8582), np.float32(0.5951), np.float32(0.6588), np.float32(0.0), np.float32(0.0), np.float32(0.7046), np.float32(0.6326), np.float32(0.9593), np.float32(0.9694)] 
+2026-10-19 05:59:00.519983: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 05:59:00.813294: lr: 0.00074 
+2026-10-19 05:59:00.813771: This epoch took 243.668961 s
+ 
+2026-10-19 05:59:00.814080: 
+epoch:  284 
+2026-10-19 06:03:14.012802: train loss : -0.8188 
+2026-10-19 06:03:19.360420: validation loss: -0.7363 
+2026-10-19 06:03:19.361441: Average global foreground Dice: [np.float32(0.932), np.float32(0.7164), np.float32(0.8635), np.float32(0.8871), np.float32(0.8032), np.float32(0.9329), np.float32(0.88), np.float32(0.7335), np.float32(0.0), np.float32(0.6146), np.float32(0.7801), np.float32(0.8424), np.float32(0.7346), np.float32(0.6255), np.float32(0.0), np.float32(0.0), np.float32(0.7953), np.float32(0.5564), np.float32(0.8027), np.float32(0.6294), np.float32(0.2651), np.float32(0.7872), np.float32(0.887), np.float32(0.897), np.float32(0.5782), np.float32(0.6459), np.float32(0.3434), np.float32(0.6667), np.float32(0.6239), np.float32(0.7007), np.float32(0.0), np.float32(0.0), np.float32(0.6999), np.float32(0.6192), np.float32(0.9367), np.float32(0.9673)] 
+2026-10-19 06:03:19.361841: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 06:03:19.647167: lr: 0.000739 
+2026-10-19 06:03:19.647585: This epoch took 258.833281 s
+ 
+2026-10-19 06:03:19.647902: 
+epoch:  285 
+2026-10-19 06:07:38.581421: train loss : -0.8154 
+2026-10-19 06:07:43.939215: validation loss: -0.7251 
+2026-10-19 06:07:43.940347: Average global foreground Dice: [np.float32(0.9444), np.float32(0.7181), np.float32(0.8568), np.float32(0.8864), np.float32(0.7885), np.float32(0.9382), np.float32(0.8862), np.float32(0.7703), np.float32(0.0), np.float32(0.5239), np.float32(0.7557), np.float32(0.8327), np.float32(0.6897), np.float32(0.6041), np.float32(0.0), np.float32(0.0), np.float32(0.8202), np.float32(0.673), np.float32(0.8463), np.float32(0.7285), np.float32(0.3157), np.float32(0.7615), np.float32(0.9268), np.float32(0.9177), np.float32(0.6465), np.float32(0.7085), np.float32(0.3944), np.float32(0.774), np.float32(0.5315), np.float32(0.7531), np.float32(0.0), np.float32(0.0), np.float32(0.7213), np.float32(0.636), np.float32(0.9523), np.float32(0.9707)] 
+2026-10-19 06:07:43.940794: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 06:07:44.244052: lr: 0.000738 
+2026-10-19 06:07:44.244434: This epoch took 264.596415 s
+ 
+2026-10-19 06:07:44.244655: 
+epoch:  286 
+2026-10-19 06:12:04.351357: train loss : -0.8138 
+2026-10-19 06:12:09.707793: validation loss: -0.7345 
+2026-10-19 06:12:09.708827: Average global foreground Dice: [np.float32(0.9298), np.float32(0.765), np.float32(0.8599), np.float32(0.8833), np.float32(0.8265), np.float32(0.9366), np.float32(0.8811), np.float32(0.7382), np.float32(0.0), np.float32(0.5457), np.float32(0.7485), np.float32(0.7972), np.float32(0.7485), np.float32(0.6502), np.float32(0.0), np.float32(0.0), np.float32(0.8358), np.float32(0.6614), np.float32(0.8344), np.float32(0.707), np.float32(0.3674), np.float32(0.782), np.float32(0.9), np.float32(0.9107), np.float32(0.6376), np.float32(0.6514), np.float32(0.3154), np.float32(0.7001), np.float32(0.6829), np.float32(0.7305), np.float32(0.0), np.float32(0.0), np.float32(0.7053), np.float32(0.5818), np.float32(0.9554), np.float32(0.9686)] 
+2026-10-19 06:12:09.709113: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 06:12:10.059839: lr: 0.000738 
+2026-10-19 06:12:10.060122: This epoch took 265.815273 s
+ 
+2026-10-19 06:12:10.060221: 
+epoch:  287 
+2026-10-19 06:16:58.350834: train loss : -0.8180 
+2026-10-19 06:17:03.712235: validation loss: -0.7308 
+2026-10-19 06:17:03.713258: Average global foreground Dice: [np.float32(0.943), np.float32(0.7354), np.float32(0.8664), np.float32(0.8845), np.float32(0.8031), np.float32(0.939), np.float32(0.8854), np.float32(0.7438), np.float32(0.0), np.float32(0.5143), np.float32(0.7496), np.float32(0.8369), np.float32(0.7215), np.float32(0.61), np.float32(0.0), np.float32(0.0), np.float32(0.8286), np.float32(0.6494), np.float32(0.8432), np.float32(0.7151), np.float32(0.3125), np.float32(0.7822), np.float32(0.9206), np.float32(0.9269), np.float32(0.6515), np.float32(0.6815), np.float32(0.3634), np.float32(0.8141), np.float32(0.5792), np.float32(0.7157), np.float32(0.0), np.float32(0.0), np.float32(0.7405), np.float32(0.6461), np.float32(0.9546), np.float32(0.9691)] 
+2026-10-19 06:17:03.714031: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 06:17:04.061963: lr: 0.000737 
+2026-10-19 06:17:04.062229: This epoch took 294.001927 s
+ 
+2026-10-19 06:17:04.062327: 
+epoch:  288 
+2026-10-19 06:21:29.205348: train loss : -0.8185 
+2026-10-19 06:21:34.583449: validation loss: -0.7430 
+2026-10-19 06:21:34.584575: Average global foreground Dice: [np.float32(0.9456), np.float32(0.7382), np.float32(0.8763), np.float32(0.8919), np.float32(0.8431), np.float32(0.9393), np.float32(0.8997), np.float32(0.6084), np.float32(0.0), np.float32(0.5987), np.float32(0.7738), np.float32(0.8326), np.float32(0.7596), np.float32(0.5571), np.float32(0.0), np.float32(0.0), np.float32(0.8342), np.float32(0.6598), np.float32(0.8438), np.float32(0.691), np.float32(0.2987), np.float32(0.7618), np.float32(0.9396), np.float32(0.9343), np.float32(0.6642), np.float32(0.6823), np.float32(0.386), np.float32(0.8131), np.float32(0.6763), np.float32(0.7972), np.float32(0.0), np.float32(0.0), np.float32(0.6675), np.float32(0.6588), np.float32(0.9604), np.float32(0.9668)] 
+2026-10-19 06:21:34.584951: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 06:21:34.883697: lr: 0.000736 
+2026-10-19 06:21:34.883968: This epoch took 270.821579 s
+ 
+2026-10-19 06:21:34.884047: 
+epoch:  289 
+2026-10-19 06:25:36.420216: train loss : -0.8230 
+2026-10-19 06:25:41.764539: validation loss: -0.7350 
+2026-10-19 06:25:41.765764: Average global foreground Dice: [np.float32(0.9445), np.float32(0.7375), np.float32(0.8454), np.float32(0.8758), np.float32(0.7882), np.float32(0.936), np.float32(0.8793), np.float32(0.7754), np.float32(0.0), np.float32(0.5334), np.float32(0.7541), np.float32(0.8264), np.float32(0.6994), np.float32(0.6663), np.float32(0.0017), np.float32(0.0), np.float32(0.8224), np.float32(0.6317), np.float32(0.8365), np.float32(0.6978), np.float32(0.2509), np.float32(0.7681), np.float32(0.9324), np.float32(0.9272), np.float32(0.6164), np.float32(0.6199), np.float32(0.3655), np.float32(0.8323), np.float32(0.5975), np.float32(0.7279), np.float32(0.0), np.float32(0.0), np.float32(0.6687), np.float32(0.6697), np.float32(0.9567), np.float32(0.9693)] 
+2026-10-19 06:25:41.766025: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 06:25:42.103151: lr: 0.000735 
+2026-10-19 06:25:42.103428: This epoch took 247.219328 s
+ 
+2026-10-19 06:25:42.103526: 
+epoch:  290 
+2026-10-19 06:30:06.288943: train loss : -0.8204 
+2026-10-19 06:30:11.654845: validation loss: -0.7513 
+2026-10-19 06:30:11.655987: Average global foreground Dice: [np.float32(0.9414), np.float32(0.7722), np.float32(0.878), np.float32(0.8877), np.float32(0.8208), np.float32(0.9294), np.float32(0.8938), np.float32(0.8149), np.float32(0.0), np.float32(0.5926), np.float32(0.7875), np.float32(0.8779), np.float32(0.7412), np.float32(0.6127), np.float32(0.0), np.float32(0.0), np.float32(0.8272), np.float32(0.6699), np.float32(0.8445), np.float32(0.7162), np.float32(0.2942), np.float32(0.7931), np.float32(0.9372), np.float32(0.9272), np.float32(0.6937), np.float32(0.6815), np.float32(0.4437), np.float32(0.8936), np.float32(0.6736), np.float32(0.8033), np.float32(0.0), np.float32(0.0), np.float32(0.6816), np.float32(0.6702), np.float32(0.9612), np.float32(0.9669)] 
+2026-10-19 06:30:11.656362: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 06:30:11.988155: lr: 0.000734 
+2026-10-19 06:30:11.988415: This epoch took 269.884512 s
+ 
+2026-10-19 06:30:11.988515: 
+epoch:  291 
+2026-10-19 06:34:09.896803: train loss : -0.8232 
+2026-10-19 06:34:15.233634: validation loss: -0.7384 
+2026-10-19 06:34:15.234778: Average global foreground Dice: [np.float32(0.9466), np.float32(0.7332), np.float32(0.8742), np.float32(0.8776), np.float32(0.7944), np.float32(0.9263), np.float32(0.8949), np.float32(0.7448), np.float32(0.0), np.float32(0.4749), np.float32(0.7627), np.float32(0.836), np.float32(0.7074), np.float32(0.6315), np.float32(0.0), np.float32(0.0), np.float32(0.829), np.float32(0.6833), np.float32(0.8485), np.float32(0.7292), np.float32(0.2764), np.float32(0.769), np.float32(0.9309), np.float32(0.928), np.float32(0.6151), np.float32(0.6877), np.float32(0.3643), np.float32(0.8338), np.float32(0.6251), np.float32(0.7645), np.float32(0.0), np.float32(0.0), np.float32(0.7056), np.float32(0.6676), np.float32(0.9611), np.float32(0.9671)] 
+2026-10-19 06:34:15.235168: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 06:34:15.535583: lr: 0.000733 
+2026-10-19 06:34:15.536027: This epoch took 243.547435 s
+ 
+2026-10-19 06:34:15.536149: 
+epoch:  292 
+2026-10-19 06:38:33.362922: train loss : -0.8152 
+2026-10-19 06:38:38.705947: validation loss: -0.7425 
+2026-10-19 06:38:38.706940: Average global foreground Dice: [np.float32(0.9385), np.float32(0.7445), np.float32(0.8659), np.float32(0.8701), np.float32(0.7827), np.float32(0.937), np.float32(0.8971), np.float32(0.8562), np.float32(0.0), np.float32(0.593), np.float32(0.756), np.float32(0.84), np.float32(0.7842), np.float32(0.6344), np.float32(0.1339), np.float32(0.0), np.float32(0.8157), np.float32(0.6508), np.float32(0.8458), np.float32(0.7091), np.float32(0.2862), np.float32(0.804), np.float32(0.8996), np.float32(0.8874), np.float32(0.6081), np.float32(0.6746), np.float32(0.3341), np.float32(0.73), np.float32(0.6101), np.float32(0.8015), np.float32(0.0), np.float32(0.0), np.float32(0.7296), np.float32(0.6099), np.float32(0.952), np.float32(0.9636)] 
+2026-10-19 06:38:38.707496: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 06:38:39.002471: lr: 0.000732 
+2026-10-19 06:38:39.002820: This epoch took 263.466611 s
+ 
+2026-10-19 06:38:39.002924: 
+epoch:  293 
+2026-10-19 06:42:28.920818: train loss : -0.8253 
+2026-10-19 06:42:34.302977: validation loss: -0.7328 
+2026-10-19 06:42:34.304223: Average global foreground Dice: [np.float32(0.9454), np.float32(0.735), np.float32(0.8742), np.float32(0.8907), np.float32(0.8047), np.float32(0.9372), np.float32(0.8861), np.float32(0.8368), np.float32(0.0), np.float32(0.5047), np.float32(0.7451), np.float32(0.8499), np.float32(0.7473), np.float32(0.5717), np.float32(0.0), np.float32(0.0), np.float32(0.8293), np.float32(0.6919), np.float32(0.844), np.float32(0.7051), np.float32(0.4079), np.float32(0.8051), np.float32(0.933), np.float32(0.9317), np.float32(0.641), np.float32(0.6394), np.float32(0.38), np.float32(0.7379), np.float32(0.5348), np.float32(0.7516), np.float32(0.0), np.float32(0.0), np.float32(0.7478), np.float32(0.6458), np.float32(0.9536), np.float32(0.966)] 
+2026-10-19 06:42:34.304745: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 06:42:34.600171: lr: 0.000731 
+2026-10-19 06:42:34.600458: This epoch took 235.597476 s
+ 
+2026-10-19 06:42:34.600537: 
+epoch:  294 
+2026-10-19 06:47:09.027235: train loss : -0.8272 
+2026-10-19 06:47:14.375296: validation loss: -0.7357 
+2026-10-19 06:47:14.376686: Average global foreground Dice: [np.float32(0.9443), np.float32(0.7735), np.float32(0.873), np.float32(0.8952), np.float32(0.8313), np.float32(0.9303), np.float32(0.8919), np.float32(0.8511), np.float32(0.0), np.float32(0.3519), np.float32(0.7573), np.float32(0.8294), np.float32(0.7809), np.float32(0.6564), np.float32(0.0), np.float32(0.0), np.float32(0.8369), np.float32(0.6827), np.float32(0.8472), np.float32(0.7249), np.float32(0.4647), np.float32(0.7926), np.float32(0.9378), np.float32(0.93), np.float32(0.6401), np.float32(0.6703), np.float32(0.4011), np.float32(0.7414), np.float32(0.6223), np.float32(0.7469), np.float32(0.0), np.float32(0.0), np.float32(0.7388), np.float32(0.6412), np.float32(0.9617), np.float32(0.9693)] 
+2026-10-19 06:47:14.376948: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 06:47:14.680994: lr: 0.00073 
+2026-10-19 06:47:14.681319: This epoch took 280.080728 s
+ 
+2026-10-19 06:47:14.681512: 
+epoch:  295 
+2026-10-19 06:51:29.712284: train loss : -0.8175 
+2026-10-19 06:51:35.069587: validation loss: -0.7357 
+2026-10-19 06:51:35.070759: Average global foreground Dice: [np.float32(0.9461), np.float32(0.7334), np.float32(0.8766), np.float32(0.8835), np.float32(0.7866), np.float32(0.9296), np.float32(0.8889), np.float32(0.7475), np.float32(0.0), np.float32(0.3484), np.float32(0.7601), np.float32(0.8524), np.float32(0.7543), np.float32(0.6166), np.float32(0.0), np.float32(0.0), np.float32(0.8223), np.float32(0.6959), np.float32(0.8367), np.float32(0.6813), np.float32(0.3014), np.float32(0.8066), np.float32(0.9347), np.float32(0.9373), np.float32(0.6776), np.float32(0.6943), np.float32(0.3947), np.float32(0.7927), np.float32(0.6637), np.float32(0.8146), np.float32(0.0), np.float32(0.0), np.float32(0.7324), np.float32(0.6422), np.float32(0.9613), np.float32(0.9691)] 
+2026-10-19 06:51:35.071017: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 06:51:35.368249: lr: 0.000729 
+2026-10-19 06:51:35.368617: This epoch took 260.686995 s
+ 
+2026-10-19 06:51:35.368747: 
+epoch:  296 
+2026-10-19 06:56:19.353452: train loss : -0.8096 
+2026-10-19 06:56:24.728082: validation loss: -0.7270 
+2026-10-19 06:56:24.729343: Average global foreground Dice: [np.float32(0.9359), np.float32(0.7526), np.float32(0.8763), np.float32(0.8799), np.float32(0.7863), np.float32(0.9239), np.float32(0.893), np.float32(0.6946), np.float32(0.0), np.float32(0.5457), np.float32(0.7699), np.float32(0.8348), np.float32(0.7647), np.float32(0.6296), np.float32(0.0), np.float32(0.0), np.float32(0.8032), np.float32(0.6586), np.float32(0.8306), np.float32(0.6882), np.float32(0.3948), np.float32(0.7958), np.float32(0.8967), np.float32(0.914), np.float32(0.6399), np.float32(0.6657), np.float32(0.4114), np.float32(0.7819), np.float32(0.5938), np.float32(0.7385), np.float32(0.0), np.float32(0.0), np.float32(0.7266), np.float32(0.6744), np.float32(0.9593), np.float32(0.9677)] 
+2026-10-19 06:56:24.729784: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 06:56:25.020676: lr: 0.000728 
+2026-10-19 06:56:25.021014: This epoch took 289.652208 s
+ 
+2026-10-19 06:56:25.021339: 
+epoch:  297 
+2026-10-19 07:00:51.083391: train loss : -0.8179 
+2026-10-19 07:00:56.469309: validation loss: -0.7258 
+2026-10-19 07:00:56.470482: Average global foreground Dice: [np.float32(0.9327), np.float32(0.7123), np.float32(0.8814), np.float32(0.8974), np.float32(0.8053), np.float32(0.9371), np.float32(0.8781), np.float32(0.6868), np.float32(0.0), np.float32(0.3775), np.float32(0.7652), np.float32(0.8499), np.float32(0.7045), np.float32(0.5925), np.float32(0.0), np.float32(0.0), np.float32(0.8229), np.float32(0.6867), np.float32(0.8458), np.float32(0.7219), np.float32(0.3533), np.float32(0.7699), np.float32(0.937), np.float32(0.9282), np.float32(0.6692), np.float32(0.6982), np.float32(0.3667), np.float32(0.8539), np.float32(0.5839), np.float32(0.7603), np.float32(0.0), np.float32(0.0), np.float32(0.7123), np.float32(0.6257), np.float32(0.959), np.float32(0.9703)] 
+2026-10-19 07:00:56.470949: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 07:00:56.761318: lr: 0.000727 
+2026-10-19 07:00:56.761808: This epoch took 271.740303 s
+ 
+2026-10-19 07:00:56.762124: 
+epoch:  298 
+2026-10-19 07:05:10.468093: train loss : -0.8235 
+2026-10-19 07:05:15.874101: validation loss: -0.7354 
+2026-10-19 07:05:15.875088: Average global foreground Dice: [np.float32(0.9405), np.float32(0.7359), np.float32(0.8751), np.float32(0.892), np.float32(0.8209), np.float32(0.9365), np.float32(0.8878), np.float32(0.6289), np.float32(0.0), np.float32(0.5105), np.float32(0.7587), np.float32(0.835), np.float32(0.7519), np.float32(0.5956), np.float32(0.0), np.float32(0.0), np.float32(0.8293), np.float32(0.679), np.float32(0.8447), np.float32(0.7032), np.float32(0.3873), np.float32(0.7526), np.float32(0.9391), np.float32(0.9261), np.float32(0.6328), np.float32(0.6921), np.float32(0.4275), np.float32(0.8376), np.float32(0.6232), np.float32(0.7739), np.float32(0.0), np.float32(0.0), np.float32(0.7379), np.float32(0.6584), np.float32(0.9607), np.float32(0.969)] 
+2026-10-19 07:05:15.875273: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 07:05:16.160795: lr: 0.000726 
+2026-10-19 07:05:16.161139: This epoch took 259.398777 s
+ 
+2026-10-19 07:05:16.161370: 
+epoch:  299 
+2026-10-19 07:10:27.858962: train loss : -0.8148 
+2026-10-19 07:10:33.212850: validation loss: -0.7307 
+2026-10-19 07:10:33.213873: Average global foreground Dice: [np.float32(0.9346), np.float32(0.7432), np.float32(0.8615), np.float32(0.8715), np.float32(0.7944), np.float32(0.9307), np.float32(0.8938), np.float32(0.7376), np.float32(0.0), np.float32(0.444), np.float32(0.7396), np.float32(0.8011), np.float32(0.7525), np.float32(0.6836), np.float32(0.0), np.float32(0.0), np.float32(0.8095), np.float32(0.6475), np.float32(0.8278), np.float32(0.653), np.float32(0.3152), np.float32(0.7986), np.float32(0.9309), np.float32(0.9176), np.float32(0.6032), np.float32(0.6479), np.float32(0.4272), np.float32(0.7899), np.float32(0.5967), np.float32(0.7167), np.float32(0.0), np.float32(0.0), np.float32(0.7456), np.float32(0.6463), np.float32(0.9454), np.float32(0.967)] 
+2026-10-19 07:10:33.214079: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 07:10:33.504229: lr: 0.000725 
+2026-10-19 07:10:33.504518: saving scheduled checkpoint file... 
+2026-10-19 07:10:33.511775: saving checkpoint... 
+2026-10-19 07:10:33.641181: done, saving took 0.14 seconds 
+2026-10-19 07:10:33.643172: done 
+2026-10-19 07:10:33.643389: This epoch took 317.481933 s
+ 
+2026-10-19 07:10:33.643556: 
+epoch:  300