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 a443e6f4dae62d2e156108835c47fcd3bee37c5b..7fa17b3b170a26a3a4f4ef2e1d7bb4d3522d06ab 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 @@
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np.float32(-0.7277048), np.float32(-0.72118944), np.float32(-0.7268921), np.float32(-0.7205211), np.float32(-0.7132519), np.float32(-0.72832817), np.float32(-0.73658645), np.float32(-0.7131482), np.float32(-0.73191917), np.float32(-0.7267002), np.float32(-0.7024312), np.float32(-0.7405727), np.float32(-0.7379684), np.float32(-0.7294525), np.float32(-0.7297472), np.float32(-0.737872), np.float32(-0.75135374), np.float32(-0.7387054), np.float32(-0.7280142), np.float32(-0.7206448), np.float32(-0.7315807), np.float32(-0.71626085), np.float32(-0.73125), np.float32(-0.72517323), np.float32(-0.73977417), np.float32(-0.72888017), np.float32(-0.7550804), np.float32(-0.7282731), np.float32(-0.7099061), np.float32(-0.7332643), np.float32(-0.7374849), np.float32(-0.7150644), np.float32(-0.73443013), np.float32(-0.7323526), np.float32(-0.7320338), np.float32(-0.7355082), np.float32(-0.72136396), np.float32(-0.7321207), np.float32(-0.7363979), np.float32(-0.7359006), np.float32(-0.73633593), np.float32(-0.7250636), np.float32(-0.7345347), np.float32(-0.7308014), np.float32(-0.7429719), np.float32(-0.734994), np.float32(-0.7513088), np.float32(-0.73836267), np.float32(-0.7424684), np.float32(-0.7327665), np.float32(-0.73568916), np.float32(-0.73567384), np.float32(-0.7270345), np.float32(-0.7258031), np.float32(-0.7353523), np.float32(-0.7307323)]",
     "all_val_losses_tr_mode": "[]",
     "also_val_in_tr_mode": "False",
-    "amp_grad_scaler": "<torch.cuda.amp.grad_scaler.GradScaler object at 0x7f1c56ffcd70>",
+    "amp_grad_scaler": "<torch.cuda.amp.grad_scaler.GradScaler object at 0x7f25364dcec0>",
     "base_num_features": "30",
     "basic_generator_patch_size": "[205 205 205]",
     "batch_dice": "False",
     "batch_size": "2",
-    "best_MA_tr_loss_for_patience": "-0.74407077",
-    "best_epoch_based_on_MA_tr_loss": "148",
-    "best_val_eval_criterion_MA": "0.59173995",
+    "best_MA_tr_loss_for_patience": "-0.81752145",
+    "best_epoch_based_on_MA_tr_loss": "294",
+    "best_val_eval_criterion_MA": "0.65192044",
     "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 0x7f1c571ee270>",
-    "dl_val": "<nnunet_mednext.training.dataloading.dataset_loading.DataLoader3D object at 0x7f1c57020e10>",
+    "dl_tr": "<nnunet_mednext.training.dataloading.dataset_loading.DataLoader3D object at 0x7f25366de3c0>",
+    "dl_val": "<nnunet_mednext.training.dataloading.dataset_loading.DataLoader3D object at 0x7f2536500e10>",
     "do_dummy_2D_aug": "False",
     "ds_loss_weights": "[0.51612903 0.25806452 0.12903226 0.06451613 0.03225806 0.        ]",
-    "epoch": "150",
+    "epoch": "300",
     "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_20_06_50.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_19_09_11_44.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: 0.0008639269723028191\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: 0.0007254178469372199\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 0x7f1c571ef8c0>",
+    "tr_gen": "<batchgenerators.dataloading.multi_threaded_augmenter.MultiThreadedAugmenter object at 0x7f25366dfa10>",
     "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 0x7f1c57021bd0>",
+    "val_gen": "<batchgenerators.dataloading.multi_threaded_augmenter.MultiThreadedAugmenter object at 0x7f2536501bd0>",
     "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 b6912cff37227697596fd0c0634e576a3ec2e7d5..c62dde7fcd01e355bc13d035717e6aa0f1e7ea0a 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 sha256:8830456b1ab692e20d3a4cdaa094d746ed600acbb9f19cb56c2993ae439e40b4
+size 127093506
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 3c6dd209b15084032d6afe28750901eb6447cfe3..61b2b5d7dc71e21e55bdbc0050115146e56f81d7 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:c2a75bb34a82531f3e54cab53309d93c73a02fa21139ea6f0ff648eb329dabda
+size 127121904
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 e37fda7eea893ab340942366c8ad08a3ed2e1682..7f3c3aa064f90c9b097931aeb5ef310cfea24cad 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:b0e00f3401d06821c5d55d7a51dd72fbcda4e92f404dc317edc9e5940f6bbaf9
-size 310264
+oid sha256:749237b64d0ae1f7560ba1db1342713f9fbd2e4fe4419f3a94e7cbd4737eebf2
+size 338444
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_19_09_11_44.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_19_09_11_44.txt
new file mode 100644
index 0000000000000000000000000000000000000000..9b812d9d2565fbf188e1368d32912e907f2d3fd0
--- /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_19_09_11_44.txt
@@ -0,0 +1,1648 @@
+Starting... 
+2026-10-19 09:11:44.926754: Using splits from existing split file: /marimo/TopBrain2026/nnUNet_preprocessed/Task001_Brain2026/splits_final.pkl 
+2026-10-19 09:11:44.927047: The split file contains 5 splits. 
+2026-10-19 09:11:44.927099: Desired fold for training: 0 
+2026-10-19 09:11:44.927145: This split has 20 training and 5 validation cases. 
+2026-10-19 09:11:45.748992: 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')]) 
+2026-10-19 09:11:45.749352: 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')]) 
+2026-10-19 09:11:47.235536: 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 
+2026-10-19 09:11:47.385297: lr: 0.000725 
+2026-10-19 09:12:07.993040: Unable to plot network architecture: 
+2026-10-19 09:12:07.994096: No module named 'hiddenlayer' 
+2026-10-19 09:12:07.994931: 
+printing the network instead:
+ 
+2026-10-19 09:12:07.995422: 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))
+  )
+) 
+2026-10-19 09:12:08.007015: 
+ 
+2026-10-19 09:12:08.007363: 
+epoch:  300 
+2026-10-19 09:16:26.094421: train loss : -0.8150 
+2026-10-19 09:16:31.477381: validation loss: -0.7422 
+2026-10-19 09:16:31.478658: Average global foreground Dice: [np.float32(0.9407), np.float32(0.7387), np.float32(0.8688), np.float32(0.8872), np.float32(0.8286), np.float32(0.9292), np.float32(0.8991), np.float32(0.7506), np.float32(0.0), np.float32(0.3785), np.float32(0.7678), np.float32(0.8157), np.float32(0.7634), np.float32(0.6271), np.float32(0.0), np.float32(0.0), np.float32(0.828), np.float32(0.6817), np.float32(0.8427), np.float32(0.7151), np.float32(0.4171), np.float32(0.7962), np.float32(0.9236), np.float32(0.9177), np.float32(0.6277), np.float32(0.6335), np.float32(0.4166), np.float32(0.8155), np.float32(0.636), np.float32(0.7711), np.float32(0.0), np.float32(0.0), np.float32(0.6979), np.float32(0.6688), np.float32(0.9576), np.float32(0.968)] 
+2026-10-19 09:16:31.479233: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 09:16:31.867570: lr: 0.000724 
+2026-10-19 09:16:31.962734: saving checkpoint... 
+2026-10-19 09:16:32.104472: done, saving took 0.24 seconds 
+2026-10-19 09:16:32.105535: This epoch took 264.097904 s
+ 
+2026-10-19 09:16:32.105703: 
+epoch:  301 
+2026-10-19 09:20:41.251862: train loss : -0.8257 
+2026-10-19 09:20:46.585400: validation loss: -0.7417 
+2026-10-19 09:20:46.586482: Average global foreground Dice: [np.float32(0.9397), np.float32(0.7289), np.float32(0.8662), np.float32(0.8902), np.float32(0.8211), np.float32(0.9314), np.float32(0.9033), np.float32(0.7935), np.float32(0.0), np.float32(0.4204), np.float32(0.7463), np.float32(0.8278), np.float32(0.7223), np.float32(0.5963), np.float32(0.0), np.float32(0.0), np.float32(0.8295), np.float32(0.6576), np.float32(0.8429), np.float32(0.6915), np.float32(0.4318), np.float32(0.7613), np.float32(0.9334), np.float32(0.9224), np.float32(0.6038), np.float32(0.6718), np.float32(0.4858), np.float32(0.7853), np.float32(0.6778), np.float32(0.7836), np.float32(0.0), np.float32(0.0), np.float32(0.7389), np.float32(0.6276), np.float32(0.9593), np.float32(0.9673)] 
+2026-10-19 09:20:46.586684: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 09:20:46.889438: lr: 0.000724 
+2026-10-19 09:20:46.948017: saving checkpoint... 
+2026-10-19 09:20:47.084376: done, saving took 0.19 seconds 
+2026-10-19 09:20:47.085838: This epoch took 254.980057 s
+ 
+2026-10-19 09:20:47.085981: 
+epoch:  302 
+2026-10-19 09:24:32.474836: train loss : -0.8183 
+2026-10-19 09:24:37.806924: validation loss: -0.7180 
+2026-10-19 09:24:37.807936: Average global foreground Dice: [np.float32(0.9447), np.float32(0.7391), np.float32(0.8628), np.float32(0.893), np.float32(0.7942), np.float32(0.9345), np.float32(0.8595), np.float32(0.7997), np.float32(0.0), np.float32(0.5391), np.float32(0.7365), np.float32(0.8097), np.float32(0.6782), np.float32(0.3052), np.float32(0.0016), np.float32(0.0), np.float32(0.8276), np.float32(0.6643), np.float32(0.8435), np.float32(0.7063), np.float32(0.3555), np.float32(0.76), np.float32(0.9214), np.float32(0.921), np.float32(0.6095), np.float32(0.6751), np.float32(0.4249), np.float32(0.8329), np.float32(0.5997), np.float32(0.7646), np.float32(0.0), np.float32(0.0), np.float32(0.7223), np.float32(0.6145), np.float32(0.9567), np.float32(0.9685)] 
+2026-10-19 09:24:37.808298: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 09:24:38.093063: lr: 0.000723 
+2026-10-19 09:24:38.093355: This epoch took 231.007295 s
+ 
+2026-10-19 09:24:38.093457: 
+epoch:  303 
+2026-10-19 09:28:34.485808: train loss : -0.8215 
+2026-10-19 09:28:39.822362: validation loss: -0.7271 
+2026-10-19 09:28:39.823350: Average global foreground Dice: [np.float32(0.9335), np.float32(0.7298), np.float32(0.854), np.float32(0.8679), np.float32(0.8071), np.float32(0.9279), np.float32(0.8973), np.float32(0.7133), np.float32(0.0), np.float32(0.5121), np.float32(0.7323), np.float32(0.8081), np.float32(0.6897), np.float32(0.6323), np.float32(0.0), np.float32(0.0), np.float32(0.8243), np.float32(0.6853), np.float32(0.8465), np.float32(0.7328), np.float32(0.4609), np.float32(0.7612), np.float32(0.9316), np.float32(0.924), np.float32(0.6021), np.float32(0.6695), np.float32(0.378), np.float32(0.8469), np.float32(0.5441), np.float32(0.7331), np.float32(0.0), np.float32(0.0), np.float32(0.7336), np.float32(0.6751), np.float32(0.9476), np.float32(0.961)] 
+2026-10-19 09:28:39.823716: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 09:28:40.116473: lr: 0.000722 
+2026-10-19 09:28:40.116732: This epoch took 242.023195 s
+ 
+2026-10-19 09:28:40.116886: 
+epoch:  304 
+2026-10-19 09:33:04.437320: train loss : -0.8137 
+2026-10-19 09:33:09.768178: validation loss: -0.7328 
+2026-10-19 09:33:09.769128: Average global foreground Dice: [np.float32(0.9414), np.float32(0.7499), np.float32(0.8479), np.float32(0.8825), np.float32(0.8194), np.float32(0.9386), np.float32(0.8892), np.float32(0.583), np.float32(0.0), np.float32(0.5692), np.float32(0.7528), np.float32(0.8008), np.float32(0.7248), np.float32(0.6174), np.float32(0.0), np.float32(0.0), np.float32(0.8258), np.float32(0.6656), np.float32(0.8332), np.float32(0.6982), np.float32(0.3468), np.float32(0.7559), np.float32(0.929), np.float32(0.9103), np.float32(0.6067), np.float32(0.6429), np.float32(0.4086), np.float32(0.7873), np.float32(0.6311), np.float32(0.7572), np.float32(0.0), np.float32(0.0), np.float32(0.7449), np.float32(0.6205), np.float32(0.959), np.float32(0.9707)] 
+2026-10-19 09:33:09.769307: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 09:33:10.090753: lr: 0.000721 
+2026-10-19 09:33:10.091002: This epoch took 269.974042 s
+ 
+2026-10-19 09:33:10.091084: 
+epoch:  305 
+2026-10-19 09:36:57.550891: train loss : -0.8280 
+2026-10-19 09:37:02.897126: validation loss: -0.7068 
+2026-10-19 09:37:02.897982: Average global foreground Dice: [np.float32(0.947), np.float32(0.6749), np.float32(0.8608), np.float32(0.8809), np.float32(0.7818), np.float32(0.9165), np.float32(0.8932), np.float32(0.5963), np.float32(0.0), np.float32(0.0007), np.float32(0.7284), np.float32(0.8093), np.float32(0.693), np.float32(0.6073), np.float32(0.0), np.float32(0.0), np.float32(0.8273), np.float32(0.6806), np.float32(0.8433), np.float32(0.6997), np.float32(0.2525), np.float32(0.7645), np.float32(0.9314), np.float32(0.9329), np.float32(0.5908), np.float32(0.6889), np.float32(0.3666), np.float32(0.8956), np.float32(0.5568), np.float32(0.741), np.float32(0.0), np.float32(0.0), np.float32(0.7308), np.float32(0.5469), np.float32(0.9464), np.float32(0.9652)] 
+2026-10-19 09:37:02.898170: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 09:37:03.186016: lr: 0.00072 
+2026-10-19 09:37:03.186274: This epoch took 233.095134 s
+ 
+2026-10-19 09:37:03.186366: 
+epoch:  306 
+2026-10-19 09:41:09.299344: train loss : -0.8099 
+2026-10-19 09:41:14.646971: validation loss: -0.7134 
+2026-10-19 09:41:14.647979: Average global foreground Dice: [np.float32(0.9458), np.float32(0.7575), np.float32(0.8823), np.float32(0.8642), np.float32(0.8263), np.float32(0.9333), np.float32(0.8883), np.float32(0.5371), np.float32(0.0), np.float32(0.4931), np.float32(0.7531), np.float32(0.8273), np.float32(0.7175), np.float32(0.5729), np.float32(0.0), np.float32(0.0), np.float32(0.8209), np.float32(0.6627), np.float32(0.8434), np.float32(0.709), np.float32(0.3695), np.float32(0.7373), np.float32(0.854), np.float32(0.8565), np.float32(0.6785), np.float32(0.703), np.float32(0.4314), np.float32(0.8009), np.float32(0.5899), np.float32(0.745), np.float32(0.0), np.float32(0.0), np.float32(0.6447), np.float32(0.6277), np.float32(0.9234), np.float32(0.9419)] 
+2026-10-19 09:41:14.648309: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 09:41:14.938194: lr: 0.000719 
+2026-10-19 09:41:14.938478: This epoch took 251.752048 s
+ 
+2026-10-19 09:41:14.938721: 
+epoch:  307 
+2026-10-19 09:45:14.826114: train loss : -0.8213 
+2026-10-19 09:45:20.169559: validation loss: -0.7406 
+2026-10-19 09:45:20.170556: Average global foreground Dice: [np.float32(0.9458), np.float32(0.6997), np.float32(0.8791), np.float32(0.8953), np.float32(0.8156), np.float32(0.9416), np.float32(0.8972), np.float32(0.5887), np.float32(0.0), np.float32(0.56), np.float32(0.7502), np.float32(0.8528), np.float32(0.7426), np.float32(0.5488), np.float32(0.0), np.float32(0.0), np.float32(0.8308), np.float32(0.7168), np.float32(0.8485), np.float32(0.7195), np.float32(0.349), np.float32(0.7473), np.float32(0.9333), np.float32(0.9291), np.float32(0.615), np.float32(0.7027), np.float32(0.4075), np.float32(0.8363), np.float32(0.6198), np.float32(0.6597), np.float32(0.0), np.float32(0.0), np.float32(0.7455), np.float32(0.6567), np.float32(0.9651), np.float32(0.9711)] 
+2026-10-19 09:45:20.170974: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 09:45:20.511414: lr: 0.000718 
+2026-10-19 09:45:20.511752: This epoch took 245.572902 s
+ 
+2026-10-19 09:45:20.511926: 
+epoch:  308 
+2026-10-19 09:49:49.678495: train loss : -0.8201 
+2026-10-19 09:49:55.020915: validation loss: -0.7293 
+2026-10-19 09:49:55.021893: Average global foreground Dice: [np.float32(0.9438), np.float32(0.7375), np.float32(0.8717), np.float32(0.9022), np.float32(0.825), np.float32(0.9403), np.float32(0.8901), np.float32(0.6019), np.float32(0.0), np.float32(0.4446), np.float32(0.7594), np.float32(0.826), np.float32(0.7433), np.float32(0.6028), np.float32(0.0), np.float32(0.0), np.float32(0.8362), np.float32(0.6817), np.float32(0.8467), np.float32(0.7037), np.float32(0.5053), np.float32(0.7477), np.float32(0.9242), np.float32(0.9244), np.float32(0.6449), np.float32(0.6836), np.float32(0.3542), np.float32(0.8064), np.float32(0.6318), np.float32(0.7311), np.float32(0.0), np.float32(0.0), np.float32(0.7516), np.float32(0.6658), np.float32(0.9598), np.float32(0.9705)] 
+2026-10-19 09:49:55.022299: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 09:49:55.348182: lr: 0.000717 
+2026-10-19 09:49:55.348397: This epoch took 274.836356 s
+ 
+2026-10-19 09:49:55.348709: 
+epoch:  309 
+2026-10-19 09:53:50.977114: train loss : -0.8309 
+2026-10-19 09:53:56.312203: validation loss: -0.7398 
+2026-10-19 09:53:56.313181: Average global foreground Dice: [np.float32(0.9452), np.float32(0.7815), np.float32(0.8736), np.float32(0.8936), np.float32(0.8136), np.float32(0.9336), np.float32(0.903), np.float32(0.6981), np.float32(0.0), np.float32(0.4402), np.float32(0.7686), np.float32(0.837), np.float32(0.755), np.float32(0.605), np.float32(0.0), np.float32(0.0), np.float32(0.8322), np.float32(0.6647), np.float32(0.8415), np.float32(0.7043), np.float32(0.4545), np.float32(0.7704), np.float32(0.9368), np.float32(0.9302), np.float32(0.6737), np.float32(0.6604), np.float32(0.3029), np.float32(0.8199), np.float32(0.6286), np.float32(0.7734), np.float32(0.0), np.float32(0.0), np.float32(0.7626), np.float32(0.6714), np.float32(0.9595), np.float32(0.9685)] 
+2026-10-19 09:53:56.313355: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 09:53:56.596693: lr: 0.000716 
+2026-10-19 09:53:56.597172: This epoch took 241.248285 s
+ 
+2026-10-19 09:53:56.597554: 
+epoch:  310 
+2026-10-19 09:58:11.606000: train loss : -0.8266 
+2026-10-19 09:58:16.954994: validation loss: -0.7386 
+2026-10-19 09:58:16.956011: Average global foreground Dice: [np.float32(0.9291), np.float32(0.7509), np.float32(0.8661), np.float32(0.892), np.float32(0.8111), np.float32(0.9273), np.float32(0.8964), np.float32(0.7243), np.float32(0.0), np.float32(0.4936), np.float32(0.7534), np.float32(0.8251), np.float32(0.6974), np.float32(0.6116), np.float32(0.0), np.float32(0.0), np.float32(0.8197), np.float32(0.6486), np.float32(0.8318), np.float32(0.6902), np.float32(0.3089), np.float32(0.745), np.float32(0.92), np.float32(0.9182), np.float32(0.6322), np.float32(0.6658), np.float32(0.3005), np.float32(0.8745), np.float32(0.6264), np.float32(0.7742), np.float32(0.0), np.float32(0.0), np.float32(0.7437), np.float32(0.6516), np.float32(0.956), np.float32(0.9647)] 
+2026-10-19 09:58:16.956257: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 09:58:17.318254: lr: 0.000715 
+2026-10-19 09:58:17.318504: This epoch took 260.720701 s
+ 
+2026-10-19 09:58:17.318597: 
+epoch:  311 
+2026-10-19 10:02:14.523896: train loss : -0.8278 
+2026-10-19 10:02:19.863794: validation loss: -0.7347 
+2026-10-19 10:02:19.864944: Average global foreground Dice: [np.float32(0.9475), np.float32(0.7666), np.float32(0.8829), np.float32(0.8912), np.float32(0.8245), np.float32(0.9353), np.float32(0.8942), np.float32(0.6653), np.float32(0.0), np.float32(0.559), np.float32(0.7725), np.float32(0.8393), np.float32(0.7053), np.float32(0.6022), np.float32(0.0), np.float32(0.0), np.float32(0.825), np.float32(0.6568), np.float32(0.8399), np.float32(0.706), np.float32(0.3366), np.float32(0.7585), np.float32(0.9295), np.float32(0.933), np.float32(0.6619), np.float32(0.6649), np.float32(0.3092), np.float32(0.8095), np.float32(0.5989), np.float32(0.7883), np.float32(0.0), np.float32(0.0), np.float32(0.7356), np.float32(0.6694), np.float32(0.9563), np.float32(0.9692)] 
+2026-10-19 10:02:19.865127: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 10:02:20.146224: lr: 0.000714 
+2026-10-19 10:02:20.146679: This epoch took 242.828014 s
+ 
+2026-10-19 10:02:20.147013: 
+epoch:  312 
+2026-10-19 10:06:54.529114: train loss : -0.8288 
+2026-10-19 10:06:59.870285: validation loss: -0.7372 
+2026-10-19 10:06:59.871931: Average global foreground Dice: [np.float32(0.9429), np.float32(0.7205), np.float32(0.8529), np.float32(0.8927), np.float32(0.7786), np.float32(0.9327), np.float32(0.8913), np.float32(0.6002), np.float32(0.0), np.float32(0.5217), np.float32(0.7622), np.float32(0.8429), np.float32(0.7426), np.float32(0.6076), np.float32(0.0), np.float32(0.0), np.float32(0.808), np.float32(0.641), np.float32(0.8253), np.float32(0.7002), np.float32(0.3314), np.float32(0.7687), np.float32(0.9335), np.float32(0.9261), np.float32(0.6112), np.float32(0.6609), np.float32(0.3434), np.float32(0.815), np.float32(0.6057), np.float32(0.7427), np.float32(0.0), np.float32(0.0), np.float32(0.7312), np.float32(0.6433), np.float32(0.9537), np.float32(0.968)] 
+2026-10-19 10:06:59.872303: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 10:07:00.142181: lr: 0.000713 
+2026-10-19 10:07:00.142617: This epoch took 279.995363 s
+ 
+2026-10-19 10:07:00.142843: 
+epoch:  313 
+2026-10-19 10:10:54.501815: train loss : -0.8247 
+2026-10-19 10:10:59.853176: validation loss: -0.7501 
+2026-10-19 10:10:59.854265: Average global foreground Dice: [np.float32(0.9412), np.float32(0.7715), np.float32(0.8635), np.float32(0.8945), np.float32(0.8204), np.float32(0.9291), np.float32(0.8941), np.float32(0.6858), np.float32(0.0), np.float32(0.6356), np.float32(0.759), np.float32(0.8217), np.float32(0.749), np.float32(0.634), np.float32(0.0), np.float32(0.0), np.float32(0.8254), np.float32(0.6665), np.float32(0.8369), np.float32(0.7082), np.float32(0.402), np.float32(0.7999), np.float32(0.9301), np.float32(0.9237), np.float32(0.6658), np.float32(0.6782), np.float32(0.4045), np.float32(0.8653), np.float32(0.6811), np.float32(0.7945), np.float32(0.0), np.float32(0.0), np.float32(0.7561), np.float32(0.652), np.float32(0.9584), np.float32(0.9687)] 
+2026-10-19 10:10:59.854512: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 10:11:00.211874: lr: 0.000712 
+2026-10-19 10:11:00.212343: This epoch took 240.069285 s
+ 
+2026-10-19 10:11:00.212611: 
+epoch:  314 
+2026-10-19 10:15:19.980268: train loss : -0.8252 
+2026-10-19 10:15:25.339815: validation loss: -0.7242 
+2026-10-19 10:15:25.340902: Average global foreground Dice: [np.float32(0.9388), np.float32(0.7531), np.float32(0.8765), np.float32(0.8888), np.float32(0.8189), np.float32(0.9266), np.float32(0.8898), np.float32(0.6959), np.float32(0.0), np.float32(0.486), np.float32(0.7497), np.float32(0.821), np.float32(0.675), np.float32(0.6032), np.float32(0.0), np.float32(0.0), np.float32(0.8377), np.float32(0.6686), np.float32(0.8451), np.float32(0.726), np.float32(0.4682), np.float32(0.8126), np.float32(0.9359), np.float32(0.925), np.float32(0.6565), np.float32(0.684), np.float32(0.4001), np.float32(0.8906), np.float32(0.4264), np.float32(0.6875), np.float32(0.0), np.float32(0.0), np.float32(0.7259), np.float32(0.6386), np.float32(0.9553), np.float32(0.9693)] 
+2026-10-19 10:15:25.341402: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 10:15:25.772517: lr: 0.000711 
+2026-10-19 10:15:25.772793: This epoch took 265.559922 s
+ 
+2026-10-19 10:15:25.772898: 
+epoch:  315 
+2026-10-19 10:19:46.894885: train loss : -0.8236 
+2026-10-19 10:19:52.241891: validation loss: -0.7400 
+2026-10-19 10:19:52.242724: Average global foreground Dice: [np.float32(0.9358), np.float32(0.7676), np.float32(0.8628), np.float32(0.8719), np.float32(0.7981), np.float32(0.9352), np.float32(0.8954), np.float32(0.5807), np.float32(0.0), np.float32(0.6053), np.float32(0.7747), np.float32(0.8345), np.float32(0.7348), np.float32(0.5439), np.float32(0.0), np.float32(0.0), np.float32(0.8358), np.float32(0.6797), np.float32(0.8448), np.float32(0.724), np.float32(0.5084), np.float32(0.7925), np.float32(0.9196), np.float32(0.9289), np.float32(0.6582), np.float32(0.687), np.float32(0.3108), np.float32(0.8646), np.float32(0.6485), np.float32(0.7308), np.float32(0.0), np.float32(0.0), np.float32(0.7083), np.float32(0.6469), np.float32(0.958), np.float32(0.9698)] 
+2026-10-19 10:19:52.242862: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 10:19:52.548367: lr: 0.00071 
+2026-10-19 10:19:52.548833: This epoch took 266.775861 s
+ 
+2026-10-19 10:19:52.549378: 
+epoch:  316 
+2026-10-19 10:23:46.373312: train loss : -0.8209 
+2026-10-19 10:23:51.714893: validation loss: -0.7308 
+2026-10-19 10:23:51.715787: Average global foreground Dice: [np.float32(0.9447), np.float32(0.7567), np.float32(0.8822), np.float32(0.8952), np.float32(0.7895), np.float32(0.9279), np.float32(0.8969), np.float32(0.6496), np.float32(0.0), np.float32(0.6432), np.float32(0.7633), np.float32(0.826), np.float32(0.7206), np.float32(0.549), np.float32(0.0), np.float32(0.0), np.float32(0.8184), np.float32(0.6531), np.float32(0.8399), np.float32(0.7103), np.float32(0.4281), np.float32(0.7642), np.float32(0.9286), np.float32(0.9364), np.float32(0.6585), np.float32(0.6846), np.float32(0.2679), np.float32(0.8216), np.float32(0.601), np.float32(0.6805), np.float32(0.0), np.float32(0.0), np.float32(0.7527), np.float32(0.6526), np.float32(0.9627), np.float32(0.9692)] 
+2026-10-19 10:23:51.715935: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 10:23:52.016512: lr: 0.00071 
+2026-10-19 10:23:52.017282: This epoch took 239.467570 s
+ 
+2026-10-19 10:23:52.017483: 
+epoch:  317 
+2026-10-19 10:28:12.914441: train loss : -0.8147 
+2026-10-19 10:28:18.264793: validation loss: -0.7334 
+2026-10-19 10:28:18.265901: Average global foreground Dice: [np.float32(0.9107), np.float32(0.6828), np.float32(0.8739), np.float32(0.8813), np.float32(0.7824), np.float32(0.9323), np.float32(0.8805), np.float32(0.6934), np.float32(0.0), np.float32(0.6106), np.float32(0.7348), np.float32(0.817), np.float32(0.6726), np.float32(0.6213), np.float32(0.0), np.float32(0.0), np.float32(0.8221), np.float32(0.6532), np.float32(0.8416), np.float32(0.7197), np.float32(0.4394), np.float32(0.773), np.float32(0.8753), np.float32(0.8972), np.float32(0.5256), np.float32(0.6486), np.float32(0.245), np.float32(0.886), np.float32(0.5567), np.float32(0.7448), np.float32(0.0), np.float32(0.0), np.float32(0.7392), np.float32(0.6721), np.float32(0.95), np.float32(0.9628)] 
+2026-10-19 10:28:18.266133: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 10:28:18.543675: lr: 0.000709 
+2026-10-19 10:28:18.543954: This epoch took 266.526300 s
+ 
+2026-10-19 10:28:18.544036: 
+epoch:  318 
+2026-10-19 10:32:33.015308: train loss : -0.8244 
+2026-10-19 10:32:38.361114: validation loss: -0.7413 
+2026-10-19 10:32:38.362138: Average global foreground Dice: [np.float32(0.9469), np.float32(0.7433), np.float32(0.8546), np.float32(0.8766), np.float32(0.7701), np.float32(0.9369), np.float32(0.8568), np.float32(0.6981), np.float32(0.0), np.float32(0.646), np.float32(0.7298), np.float32(0.8035), np.float32(0.7287), np.float32(0.5987), np.float32(0.0), np.float32(0.0), np.float32(0.8096), np.float32(0.6016), np.float32(0.8264), np.float32(0.6868), np.float32(0.4211), np.float32(0.7511), np.float32(0.924), np.float32(0.9208), np.float32(0.7033), np.float32(0.6585), np.float32(0.3467), np.float32(0.8384), np.float32(0.5939), np.float32(0.7598), np.float32(0.0), np.float32(0.0), np.float32(0.7391), np.float32(0.6541), np.float32(0.9601), np.float32(0.9613)] 
+2026-10-19 10:32:38.362313: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 10:32:38.676433: lr: 0.000708 
+2026-10-19 10:32:38.676728: This epoch took 260.132631 s
+ 
+2026-10-19 10:32:38.677024: 
+epoch:  319 
+2026-10-19 10:37:22.251417: train loss : -0.8155 
+2026-10-19 10:37:27.604103: validation loss: -0.7086 
+2026-10-19 10:37:27.605233: Average global foreground Dice: [np.float32(0.9302), np.float32(0.7005), np.float32(0.8777), np.float32(0.8625), np.float32(0.6997), np.float32(0.9154), np.float32(0.8771), np.float32(0.3684), np.float32(0.0), np.float32(0.6005), np.float32(0.719), np.float32(0.8014), np.float32(0.7202), np.float32(0.597), np.float32(0.0015), np.float32(0.0), np.float32(0.8062), np.float32(0.647), np.float32(0.8381), np.float32(0.711), np.float32(0.4036), np.float32(0.7982), np.float32(0.9261), np.float32(0.9204), np.float32(0.6585), np.float32(0.6663), np.float32(0.2723), np.float32(0.7934), np.float32(0.645), np.float32(0.7945), np.float32(0.0), np.float32(0.0), np.float32(0.6452), np.float32(0.6455), np.float32(0.9623), np.float32(0.9693)] 
+2026-10-19 10:37:27.605467: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 10:37:27.926537: lr: 0.000707 
+2026-10-19 10:37:27.926792: This epoch took 289.249680 s
+ 
+2026-10-19 10:37:27.926888: 
+epoch:  320 
+2026-10-19 10:41:46.454198: train loss : -0.8242 
+2026-10-19 10:41:51.813021: validation loss: -0.7420 
+2026-10-19 10:41:51.813853: Average global foreground Dice: [np.float32(0.9402), np.float32(0.7374), np.float32(0.8533), np.float32(0.8974), np.float32(0.8235), np.float32(0.9298), np.float32(0.9058), np.float32(0.69), np.float32(0.0), np.float32(0.6518), np.float32(0.7677), np.float32(0.8526), np.float32(0.7121), np.float32(0.6463), np.float32(0.0), np.float32(0.0), np.float32(0.816), np.float32(0.6229), np.float32(0.8307), np.float32(0.7065), np.float32(0.3678), np.float32(0.7724), np.float32(0.9026), np.float32(0.9064), np.float32(0.6113), np.float32(0.6659), np.float32(0.3199), np.float32(0.7827), np.float32(0.6214), np.float32(0.7272), np.float32(0.0), np.float32(0.0), np.float32(0.6801), np.float32(0.6538), np.float32(0.9569), np.float32(0.969)] 
+2026-10-19 10:41:51.814006: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 10:41:52.090365: lr: 0.000706 
+2026-10-19 10:41:52.090721: This epoch took 264.163765 s
+ 
+2026-10-19 10:41:52.090945: 
+epoch:  321 
+2026-10-19 10:45:17.576091: train loss : -0.8230 
+2026-10-19 10:45:22.925057: validation loss: -0.7341 
+2026-10-19 10:45:22.926000: Average global foreground Dice: [np.float32(0.9449), np.float32(0.7423), np.float32(0.8638), np.float32(0.8909), np.float32(0.8056), np.float32(0.9319), np.float32(0.8991), np.float32(0.462), np.float32(0.0), np.float32(0.6091), np.float32(0.7572), np.float32(0.8187), np.float32(0.6705), np.float32(0.4169), np.float32(0.0), np.float32(0.0308), np.float32(0.8395), np.float32(0.6568), np.float32(0.8449), np.float32(0.7179), np.float32(0.3943), np.float32(0.7743), np.float32(0.9286), np.float32(0.9293), np.float32(0.6511), np.float32(0.6823), np.float32(0.3913), np.float32(0.839), np.float32(0.6327), np.float32(0.7642), np.float32(0.0), np.float32(0.0), np.float32(0.7194), np.float32(0.6602), np.float32(0.9615), np.float32(0.9711)] 
+2026-10-19 10:45:22.926153: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 10:45:23.206808: lr: 0.000705 
+2026-10-19 10:45:23.207232: This epoch took 211.116062 s
+ 
+2026-10-19 10:45:23.207538: 
+epoch:  322 
+2026-10-19 10:49:12.925946: train loss : -0.8294 
+2026-10-19 10:49:18.289259: validation loss: -0.7379 
+2026-10-19 10:49:18.290309: Average global foreground Dice: [np.float32(0.9471), np.float32(0.7524), np.float32(0.874), np.float32(0.9005), np.float32(0.788), np.float32(0.9341), np.float32(0.8951), np.float32(0.6873), np.float32(0.0), np.float32(0.621), np.float32(0.7566), np.float32(0.8276), np.float32(0.7146), np.float32(0.6403), np.float32(0.0), np.float32(0.0), np.float32(0.8271), np.float32(0.6522), np.float32(0.8412), np.float32(0.7133), np.float32(0.4391), np.float32(0.7802), np.float32(0.9319), np.float32(0.9284), np.float32(0.6649), np.float32(0.6569), np.float32(0.335), np.float32(0.8022), np.float32(0.612), np.float32(0.7743), np.float32(0.0), np.float32(0.0), np.float32(0.7229), np.float32(0.6537), np.float32(0.9605), np.float32(0.9699)] 
+2026-10-19 10:49:18.290594: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 10:49:18.637932: lr: 0.000704 
+2026-10-19 10:49:18.638361: This epoch took 235.430585 s
+ 
+2026-10-19 10:49:18.638548: 
+epoch:  323 
+2026-10-19 10:53:43.281557: train loss : -0.8248 
+2026-10-19 10:53:48.630153: validation loss: -0.7496 
+2026-10-19 10:53:48.631801: Average global foreground Dice: [np.float32(0.9433), np.float32(0.8062), np.float32(0.8728), np.float32(0.8998), np.float32(0.8246), np.float32(0.9314), np.float32(0.8947), np.float32(0.7257), np.float32(0.0), np.float32(0.5801), np.float32(0.7397), np.float32(0.8127), np.float32(0.7528), np.float32(0.6372), np.float32(0.0), np.float32(0.0), np.float32(0.8334), np.float32(0.6605), np.float32(0.8378), np.float32(0.7051), np.float32(0.5611), np.float32(0.7722), np.float32(0.9275), np.float32(0.927), np.float32(0.6543), np.float32(0.6501), np.float32(0.3793), np.float32(0.8032), np.float32(0.6651), np.float32(0.7603), np.float32(0.0), np.float32(0.0), np.float32(0.7224), np.float32(0.6178), np.float32(0.9618), np.float32(0.97)] 
+2026-10-19 10:53:48.632120: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 10:53:48.934144: lr: 0.000703 
+2026-10-19 10:53:48.934688: This epoch took 270.295942 s
+ 
+2026-10-19 10:53:48.935014: 
+epoch:  324 
+2026-10-19 10:58:05.329986: train loss : -0.8279 
+2026-10-19 10:58:10.682302: validation loss: -0.7327 
+2026-10-19 10:58:10.683427: Average global foreground Dice: [np.float32(0.9401), np.float32(0.7411), np.float32(0.8645), np.float32(0.8717), np.float32(0.7869), np.float32(0.9228), np.float32(0.899), np.float32(0.6895), np.float32(0.0), np.float32(0.5619), np.float32(0.7422), np.float32(0.8282), np.float32(0.7544), np.float32(0.6523), np.float32(0.0), np.float32(0.0), np.float32(0.8149), np.float32(0.6625), np.float32(0.8385), np.float32(0.709), np.float32(0.3256), np.float32(0.7587), np.float32(0.928), np.float32(0.9276), np.float32(0.657), np.float32(0.6793), np.float32(0.2885), np.float32(0.8478), np.float32(0.552), np.float32(0.7518), np.float32(0.0), np.float32(0.0), np.float32(0.7476), np.float32(0.6495), np.float32(0.9582), np.float32(0.9686)] 
+2026-10-19 10:58:10.683741: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 10:58:10.976885: lr: 0.000702 
+2026-10-19 10:58:10.977202: This epoch took 262.041877 s
+ 
+2026-10-19 10:58:10.977463: 
+epoch:  325 
+2026-10-19 11:02:41.485528: train loss : -0.8215 
+2026-10-19 11:02:46.839878: validation loss: -0.7205 
+2026-10-19 11:02:46.840765: Average global foreground Dice: [np.float32(0.9408), np.float32(0.7406), np.float32(0.8483), np.float32(0.8922), np.float32(0.7775), np.float32(0.9319), np.float32(0.8846), np.float32(0.7949), np.float32(0.0), np.float32(0.5474), np.float32(0.7352), np.float32(0.804), np.float32(0.6617), np.float32(0.6622), np.float32(0.0), np.float32(0.0), np.float32(0.8178), np.float32(0.6576), np.float32(0.8366), np.float32(0.7141), np.float32(0.3425), np.float32(0.7812), np.float32(0.9319), np.float32(0.9271), np.float32(0.6511), np.float32(0.6251), np.float32(0.3372), np.float32(0.8459), np.float32(0.5282), np.float32(0.7172), np.float32(0.0), np.float32(0.0), np.float32(0.7329), np.float32(0.6614), np.float32(0.95), np.float32(0.9674)] 
+2026-10-19 11:02:46.840987: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 11:02:47.140333: lr: 0.000701 
+2026-10-19 11:02:47.140622: This epoch took 276.163041 s
+ 
+2026-10-19 11:02:47.140725: 
+epoch:  326 
+2026-10-19 11:06:38.185734: train loss : -0.8239 
+2026-10-19 11:06:43.537533: validation loss: -0.7443 
+2026-10-19 11:06:43.538562: Average global foreground Dice: [np.float32(0.9412), np.float32(0.7511), np.float32(0.8758), np.float32(0.9043), np.float32(0.8326), np.float32(0.9282), np.float32(0.8885), np.float32(0.7186), np.float32(0.0), np.float32(0.6336), np.float32(0.7599), np.float32(0.837), np.float32(0.7474), np.float32(0.5808), np.float32(0.0), np.float32(0.0), np.float32(0.8284), np.float32(0.6692), np.float32(0.8447), np.float32(0.7249), np.float32(0.3555), np.float32(0.793), np.float32(0.9367), np.float32(0.9316), np.float32(0.69), np.float32(0.6741), np.float32(0.3664), np.float32(0.8302), np.float32(0.6401), np.float32(0.7836), np.float32(0.0), np.float32(0.0), np.float32(0.7509), np.float32(0.6464), np.float32(0.9612), np.float32(0.9694)] 
+2026-10-19 11:06:43.539024: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 11:06:43.828907: lr: 0.0007 
+2026-10-19 11:06:43.829206: This epoch took 236.688404 s
+ 
+2026-10-19 11:06:43.829456: 
+epoch:  327 
+2026-10-19 11:10:45.941116: train loss : -0.8295 
+2026-10-19 11:10:51.292343: validation loss: -0.7337 
+2026-10-19 11:10:51.293737: Average global foreground Dice: [np.float32(0.9349), np.float32(0.7283), np.float32(0.8656), np.float32(0.8869), np.float32(0.8017), np.float32(0.9233), np.float32(0.8865), np.float32(0.7339), np.float32(0.0), np.float32(0.6232), np.float32(0.7519), np.float32(0.8386), np.float32(0.7279), np.float32(0.5984), np.float32(0.0), np.float32(0.0), np.float32(0.8215), np.float32(0.648), np.float32(0.8374), np.float32(0.7023), np.float32(0.4262), np.float32(0.7569), np.float32(0.9061), np.float32(0.904), np.float32(0.6338), np.float32(0.692), np.float32(0.3489), np.float32(0.8718), np.float32(0.4748), np.float32(0.7), np.float32(0.0), np.float32(0.0), np.float32(0.73), np.float32(0.6542), np.float32(0.9559), np.float32(0.9673)] 
+2026-10-19 11:10:51.294197: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 11:10:51.579773: lr: 0.000699 
+2026-10-19 11:10:51.580111: This epoch took 247.750429 s
+ 
+2026-10-19 11:10:51.580314: 
+epoch:  328 
+2026-10-19 11:14:54.824082: train loss : -0.8240 
+2026-10-19 11:15:00.168861: validation loss: -0.7401 
+2026-10-19 11:15:00.169897: Average global foreground Dice: [np.float32(0.9422), np.float32(0.7617), np.float32(0.8668), np.float32(0.8867), np.float32(0.792), np.float32(0.9349), np.float32(0.887), np.float32(0.7047), np.float32(0.0), np.float32(0.3403), np.float32(0.7445), np.float32(0.8181), np.float32(0.6783), np.float32(0.6528), np.float32(0.0), np.float32(0.0), np.float32(0.8317), np.float32(0.6586), np.float32(0.8423), np.float32(0.7124), np.float32(0.4054), np.float32(0.771), np.float32(0.9311), np.float32(0.9335), np.float32(0.6268), np.float32(0.6678), np.float32(0.331), np.float32(0.8288), np.float32(0.6068), np.float32(0.8065), np.float32(0.0), np.float32(0.0), np.float32(0.7507), np.float32(0.6546), np.float32(0.9593), np.float32(0.9709)] 
+2026-10-19 11:15:00.170309: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 11:15:00.455847: lr: 0.000698 
+2026-10-19 11:15:00.456146: This epoch took 248.875506 s
+ 
+2026-10-19 11:15:00.456299: 
+epoch:  329 
+2026-10-19 11:19:09.843707: train loss : -0.8179 
+2026-10-19 11:19:15.187878: validation loss: -0.7528 
+2026-10-19 11:19:15.188832: Average global foreground Dice: [np.float32(0.9429), np.float32(0.7737), np.float32(0.8615), np.float32(0.8975), np.float32(0.7966), np.float32(0.9226), np.float32(0.8994), np.float32(0.6279), np.float32(0.0), np.float32(0.4756), np.float32(0.7455), np.float32(0.8328), np.float32(0.7512), np.float32(0.6779), np.float32(0.0), np.float32(0.0), np.float32(0.8262), np.float32(0.6536), np.float32(0.8393), np.float32(0.7141), np.float32(0.3806), np.float32(0.7833), np.float32(0.9359), np.float32(0.9326), np.float32(0.6849), np.float32(0.6578), np.float32(0.364), np.float32(0.8318), np.float32(0.6824), np.float32(0.8003), np.float32(0.0), np.float32(0.0), np.float32(0.7599), np.float32(0.6571), np.float32(0.9642), np.float32(0.9669)] 
+2026-10-19 11:19:15.189164: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 11:19:15.517327: lr: 0.000697 
+2026-10-19 11:19:15.517674: This epoch took 255.061304 s
+ 
+2026-10-19 11:19:15.518045: 
+epoch:  330 
+2026-10-19 11:23:29.767388: train loss : -0.8231 
+2026-10-19 11:23:35.123080: validation loss: -0.7486 
+2026-10-19 11:23:35.124099: Average global foreground Dice: [np.float32(0.942), np.float32(0.7693), np.float32(0.84), np.float32(0.8966), np.float32(0.8052), np.float32(0.9288), np.float32(0.8888), np.float32(0.7165), np.float32(0.0), np.float32(0.5772), np.float32(0.7453), np.float32(0.8153), np.float32(0.7548), np.float32(0.6512), np.float32(0.0), np.float32(0.0), np.float32(0.8137), np.float32(0.6463), np.float32(0.8322), np.float32(0.7134), np.float32(0.3097), np.float32(0.7858), np.float32(0.9321), np.float32(0.9264), np.float32(0.6736), np.float32(0.6433), np.float32(0.3223), np.float32(0.8964), np.float32(0.6484), np.float32(0.7058), np.float32(0.0), np.float32(0.0), np.float32(0.743), np.float32(0.6284), np.float32(0.9641), np.float32(0.9689)] 
+2026-10-19 11:23:35.124300: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 11:23:35.442696: lr: 0.000696 
+2026-10-19 11:23:35.442969: This epoch took 259.924659 s
+ 
+2026-10-19 11:23:35.443055: 
+epoch:  331 
+2026-10-19 11:27:22.011620: train loss : -0.8302 
+2026-10-19 11:27:27.358583: validation loss: -0.7319 
+2026-10-19 11:27:27.359808: Average global foreground Dice: [np.float32(0.9482), np.float32(0.7431), np.float32(0.8413), np.float32(0.9017), np.float32(0.7982), np.float32(0.9359), np.float32(0.8815), np.float32(0.7495), np.float32(0.0), np.float32(0.5356), np.float32(0.7314), np.float32(0.8031), np.float32(0.7482), np.float32(0.6104), np.float32(0.0), np.float32(0.0), np.float32(0.8212), np.float32(0.675), np.float32(0.8348), np.float32(0.7042), np.float32(0.3797), np.float32(0.7369), np.float32(0.9247), np.float32(0.9201), np.float32(0.6292), np.float32(0.7058), np.float32(0.429), np.float32(0.8259), np.float32(0.6193), np.float32(0.7041), np.float32(0.0), np.float32(0.0), np.float32(0.7468), np.float32(0.6355), np.float32(0.9585), np.float32(0.9697)] 
+2026-10-19 11:27:27.360211: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 11:27:27.712749: lr: 0.000696 
+2026-10-19 11:27:27.712957: This epoch took 232.269832 s
+ 
+2026-10-19 11:27:27.713055: 
+epoch:  332 
+2026-10-19 11:31:32.998125: train loss : -0.8290 
+2026-10-19 11:31:38.332500: validation loss: -0.7367 
+2026-10-19 11:31:38.333455: Average global foreground Dice: [np.float32(0.9486), np.float32(0.7859), np.float32(0.8657), np.float32(0.911), np.float32(0.8206), np.float32(0.9349), np.float32(0.8918), np.float32(0.7397), np.float32(0.0), np.float32(0.5425), np.float32(0.7517), np.float32(0.8143), np.float32(0.736), np.float32(0.6459), np.float32(0.0), np.float32(0.0), np.float32(0.8354), np.float32(0.6814), np.float32(0.843), np.float32(0.725), np.float32(0.3877), np.float32(0.7847), np.float32(0.932), np.float32(0.9233), np.float32(0.6494), np.float32(0.668), np.float32(0.3065), np.float32(0.8138), np.float32(0.7002), np.float32(0.7547), np.float32(0.0), np.float32(0.0), np.float32(0.7581), np.float32(0.6515), np.float32(0.9589), np.float32(0.971)] 
+2026-10-19 11:31:38.333758: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 11:31:38.656675: lr: 0.000695 
+2026-10-19 11:31:38.657045: This epoch took 250.943923 s
+ 
+2026-10-19 11:31:38.657256: 
+epoch:  333 
+2026-10-19 11:35:38.553590: train loss : -0.8266 
+2026-10-19 11:35:43.896932: validation loss: -0.7192 
+2026-10-19 11:35:43.897926: Average global foreground Dice: [np.float32(0.9414), np.float32(0.7473), np.float32(0.8635), np.float32(0.8941), np.float32(0.7922), np.float32(0.9192), np.float32(0.8897), np.float32(0.7173), np.float32(0.0), np.float32(0.27), np.float32(0.7445), np.float32(0.8197), np.float32(0.7669), np.float32(0.6581), np.float32(0.0), np.float32(0.0), np.float32(0.8231), np.float32(0.6625), np.float32(0.8343), np.float32(0.6972), np.float32(0.3024), np.float32(0.7655), np.float32(0.9094), np.float32(0.912), np.float32(0.6247), np.float32(0.6292), np.float32(0.2275), np.float32(0.6435), np.float32(0.5654), np.float32(0.7395), np.float32(0.0), np.float32(0.0), np.float32(0.7612), np.float32(0.6674), np.float32(0.9569), np.float32(0.9673)] 
+2026-10-19 11:35:43.898117: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 11:35:44.179810: lr: 0.000694 
+2026-10-19 11:35:44.180034: This epoch took 245.522696 s
+ 
+2026-10-19 11:35:44.180114: 
+epoch:  334 
+2026-10-19 11:39:29.977643: train loss : -0.8314 
+2026-10-19 11:39:35.324363: validation loss: -0.7350 
+2026-10-19 11:39:35.325506: Average global foreground Dice: [np.float32(0.941), np.float32(0.7259), np.float32(0.8594), np.float32(0.8795), np.float32(0.7966), np.float32(0.9315), np.float32(0.9001), np.float32(0.8163), np.float32(0.0), np.float32(0.6341), np.float32(0.7736), np.float32(0.8339), np.float32(0.7295), np.float32(0.5826), np.float32(0.0054), np.float32(0.0), np.float32(0.8251), np.float32(0.6597), np.float32(0.8468), np.float32(0.7026), np.float32(0.2214), np.float32(0.7736), np.float32(0.9159), np.float32(0.9234), np.float32(0.6465), np.float32(0.6817), np.float32(0.2824), np.float32(0.8312), np.float32(0.5659), np.float32(0.7834), np.float32(0.0), np.float32(0.0), np.float32(0.6164), np.float32(0.6145), np.float32(0.9481), np.float32(0.9676)] 
+2026-10-19 11:39:35.326042: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 11:39:35.620780: lr: 0.000693 
+2026-10-19 11:39:35.621035: This epoch took 231.440869 s
+ 
+2026-10-19 11:39:35.621112: 
+epoch:  335 
+2026-10-19 11:43:49.078221: train loss : -0.8231 
+2026-10-19 11:43:54.426561: validation loss: -0.7279 
+2026-10-19 11:43:54.427617: Average global foreground Dice: [np.float32(0.9422), np.float32(0.7322), np.float32(0.847), np.float32(0.8946), np.float32(0.7967), np.float32(0.9358), np.float32(0.8957), np.float32(0.7669), np.float32(0.0), np.float32(0.6212), np.float32(0.7577), np.float32(0.8212), np.float32(0.7383), np.float32(0.6449), np.float32(0.0), np.float32(0.0), np.float32(0.8294), np.float32(0.6718), np.float32(0.8489), np.float32(0.7131), np.float32(0.2858), np.float32(0.7694), np.float32(0.9262), np.float32(0.9186), np.float32(0.6253), np.float32(0.6491), np.float32(0.3937), np.float32(0.8759), np.float32(0.5728), np.float32(0.7666), np.float32(0.0), np.float32(0.0), np.float32(0.7391), np.float32(0.6461), np.float32(0.9504), np.float32(0.9708)] 
+2026-10-19 11:43:54.427821: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 11:43:54.715171: lr: 0.000692 
+2026-10-19 11:43:54.715423: This epoch took 259.094257 s
+ 
+2026-10-19 11:43:54.715521: 
+epoch:  336 
+2026-10-19 11:48:05.507471: train loss : -0.8268 
+2026-10-19 11:48:10.842241: validation loss: -0.7360 
+2026-10-19 11:48:10.843482: Average global foreground Dice: [np.float32(0.9428), np.float32(0.7255), np.float32(0.8723), np.float32(0.8937), np.float32(0.7949), np.float32(0.933), np.float32(0.8913), np.float32(0.5706), np.float32(0.0), np.float32(0.6049), np.float32(0.754), np.float32(0.8243), np.float32(0.7531), np.float32(0.6303), np.float32(0.0), np.float32(0.0), np.float32(0.8308), np.float32(0.6592), np.float32(0.8434), np.float32(0.6997), np.float32(0.35), np.float32(0.7617), np.float32(0.9341), np.float32(0.9244), np.float32(0.6559), np.float32(0.7078), np.float32(0.4), np.float32(0.8538), np.float32(0.6179), np.float32(0.7594), np.float32(0.0), np.float32(0.0), np.float32(0.7221), np.float32(0.6493), np.float32(0.9592), np.float32(0.9695)] 
+2026-10-19 11:48:10.844153: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 11:48:11.140966: lr: 0.000691 
+2026-10-19 11:48:11.141228: This epoch took 256.425642 s
+ 
+2026-10-19 11:48:11.141548: 
+epoch:  337 
+2026-10-19 11:52:30.751859: train loss : -0.8220 
+2026-10-19 11:52:36.120409: validation loss: -0.7457 
+2026-10-19 11:52:36.121643: Average global foreground Dice: [np.float32(0.9443), np.float32(0.7457), np.float32(0.8457), np.float32(0.8954), np.float32(0.8141), np.float32(0.9264), np.float32(0.9002), np.float32(0.6561), np.float32(0.0), np.float32(0.6073), np.float32(0.7683), np.float32(0.828), np.float32(0.766), np.float32(0.5834), np.float32(0.0), np.float32(0.0), np.float32(0.822), np.float32(0.6399), np.float32(0.8258), np.float32(0.7001), np.float32(0.3064), np.float32(0.7525), np.float32(0.9298), np.float32(0.9258), np.float32(0.6358), np.float32(0.6976), np.float32(0.375), np.float32(0.8343), np.float32(0.6724), np.float32(0.7709), np.float32(0.0), np.float32(0.0), np.float32(0.7665), np.float32(0.6392), np.float32(0.9605), np.float32(0.9686)] 
+2026-10-19 11:52:36.121998: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 11:52:36.407581: lr: 0.00069 
+2026-10-19 11:52:36.407984: This epoch took 265.266350 s
+ 
+2026-10-19 11:52:36.408219: 
+epoch:  338 
+2026-10-19 11:56:32.602351: train loss : -0.8356 
+2026-10-19 11:56:37.954531: validation loss: -0.7495 
+2026-10-19 11:56:37.955710: Average global foreground Dice: [np.float32(0.9452), np.float32(0.7671), np.float32(0.8562), np.float32(0.8905), np.float32(0.7836), np.float32(0.9356), np.float32(0.9097), np.float32(0.6276), np.float32(0.0), np.float32(0.556), np.float32(0.7621), np.float32(0.8295), np.float32(0.7628), np.float32(0.6627), np.float32(0.0), np.float32(0.0), np.float32(0.8264), np.float32(0.6598), np.float32(0.8436), np.float32(0.7073), np.float32(0.3152), np.float32(0.7997), np.float32(0.9371), np.float32(0.9257), np.float32(0.6336), np.float32(0.6939), np.float32(0.4184), np.float32(0.8596), np.float32(0.679), np.float32(0.752), np.float32(0.0), np.float32(0.0), np.float32(0.7054), np.float32(0.6207), np.float32(0.9564), np.float32(0.9688)] 
+2026-10-19 11:56:37.955923: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 11:56:38.249309: lr: 0.000689 
+2026-10-19 11:56:38.249680: This epoch took 241.841276 s
+ 
+2026-10-19 11:56:38.249817: 
+epoch:  339 
+2026-10-19 12:00:25.197738: train loss : -0.8282 
+2026-10-19 12:00:30.563576: validation loss: -0.7463 
+2026-10-19 12:00:30.564695: Average global foreground Dice: [np.float32(0.9451), np.float32(0.7505), np.float32(0.8613), np.float32(0.8807), np.float32(0.7885), np.float32(0.9355), np.float32(0.8925), np.float32(0.7725), np.float32(0.0), np.float32(0.6261), np.float32(0.7838), np.float32(0.838), np.float32(0.736), np.float32(0.6316), np.float32(0.0), np.float32(0.0), np.float32(0.8216), np.float32(0.6499), np.float32(0.8327), np.float32(0.6958), np.float32(0.2866), np.float32(0.7613), np.float32(0.9276), np.float32(0.924), np.float32(0.6355), np.float32(0.6824), np.float32(0.4544), np.float32(0.863), np.float32(0.6624), np.float32(0.7366), np.float32(0.0), np.float32(0.0), np.float32(0.7678), np.float32(0.6484), np.float32(0.9596), np.float32(0.9694)] 
+2026-10-19 12:00:30.564909: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 12:00:30.913863: lr: 0.000688 
+2026-10-19 12:00:30.914145: This epoch took 232.664260 s
+ 
+2026-10-19 12:00:30.914228: 
+epoch:  340 
+2026-10-19 12:04:26.138931: train loss : -0.8294 
+2026-10-19 12:04:31.478829: validation loss: -0.7351 
+2026-10-19 12:04:31.479784: Average global foreground Dice: [np.float32(0.9476), np.float32(0.751), np.float32(0.8737), np.float32(0.8916), np.float32(0.8071), np.float32(0.9339), np.float32(0.8909), np.float32(0.6263), np.float32(0.0), np.float32(0.5962), np.float32(0.7569), np.float32(0.8289), np.float32(0.6524), np.float32(0.6535), np.float32(0.0), np.float32(0.0), np.float32(0.8265), np.float32(0.6676), np.float32(0.8465), np.float32(0.7151), np.float32(0.3108), np.float32(0.7868), np.float32(0.9365), np.float32(0.9274), np.float32(0.6674), np.float32(0.6933), np.float32(0.4479), np.float32(0.8716), np.float32(0.6612), np.float32(0.82), np.float32(0.0), np.float32(0.0), np.float32(0.7357), np.float32(0.6584), np.float32(0.9598), np.float32(0.9703)] 
+2026-10-19 12:04:31.480179: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 12:04:31.768426: lr: 0.000687 
+2026-10-19 12:04:31.768909: This epoch took 240.854626 s
+ 
+2026-10-19 12:04:31.769041: 
+epoch:  341 
+2026-10-19 12:08:22.509040: train loss : -0.8316 
+2026-10-19 12:08:27.861027: validation loss: -0.7296 
+2026-10-19 12:08:27.862020: Average global foreground Dice: [np.float32(0.9414), np.float32(0.7488), np.float32(0.8727), np.float32(0.8955), np.float32(0.7987), np.float32(0.9326), np.float32(0.8846), np.float32(0.7509), np.float32(0.0), np.float32(0.5941), np.float32(0.7363), np.float32(0.8279), np.float32(0.6775), np.float32(0.5782), np.float32(0.0), np.float32(0.0), np.float32(0.8187), np.float32(0.6746), np.float32(0.8427), np.float32(0.735), np.float32(0.3478), np.float32(0.8076), np.float32(0.9294), np.float32(0.9296), np.float32(0.6543), np.float32(0.6689), np.float32(0.3832), np.float32(0.8305), np.float32(0.6391), np.float32(0.721), np.float32(0.0), np.float32(0.0), np.float32(0.7361), np.float32(0.6599), np.float32(0.9592), np.float32(0.969)] 
+2026-10-19 12:08:27.862500: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 12:08:28.154169: lr: 0.000686 
+2026-10-19 12:08:28.154589: This epoch took 236.385473 s
+ 
+2026-10-19 12:08:28.154838: 
+epoch:  342 
+2026-10-19 12:13:14.394619: train loss : -0.8236 
+2026-10-19 12:13:19.755302: validation loss: -0.7404 
+2026-10-19 12:13:19.756211: Average global foreground Dice: [np.float32(0.9426), np.float32(0.7391), np.float32(0.8833), np.float32(0.9012), np.float32(0.8111), np.float32(0.9276), np.float32(0.8951), np.float32(0.5845), np.float32(0.0), np.float32(0.6108), np.float32(0.7651), np.float32(0.8201), np.float32(0.7138), np.float32(0.5243), np.float32(0.1114), np.float32(0.0), np.float32(0.8291), np.float32(0.6597), np.float32(0.8444), np.float32(0.7193), np.float32(0.4669), np.float32(0.8242), np.float32(0.9302), np.float32(0.935), np.float32(0.6452), np.float32(0.707), np.float32(0.4057), np.float32(0.851), np.float32(0.6493), np.float32(0.7339), np.float32(0.0), np.float32(0.0), np.float32(0.7369), np.float32(0.6749), np.float32(0.9607), np.float32(0.9706)] 
+2026-10-19 12:13:19.756472: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 12:13:20.083779: lr: 0.000685 
+2026-10-19 12:13:20.084150: This epoch took 291.929172 s
+ 
+2026-10-19 12:13:20.084403: 
+epoch:  343 
+2026-10-19 12:17:22.872530: train loss : -0.8283 
+2026-10-19 12:17:28.220911: validation loss: -0.7115 
+2026-10-19 12:17:28.222300: Average global foreground Dice: [np.float32(0.9332), np.float32(0.6965), np.float32(0.8786), np.float32(0.826), np.float32(0.7427), np.float32(0.9107), np.float32(0.8951), np.float32(0.7311), np.float32(0.0), np.float32(0.6657), np.float32(0.7504), np.float32(0.7943), np.float32(0.6705), np.float32(0.6316), np.float32(0.0699), np.float32(0.0), np.float32(0.8259), np.float32(0.6823), np.float32(0.8486), np.float32(0.7092), np.float32(0.2699), np.float32(0.7864), np.float32(0.9098), np.float32(0.9025), np.float32(0.6077), np.float32(0.6964), np.float32(0.3505), np.float32(0.8294), np.float32(0.5132), np.float32(0.72), np.float32(0.0), np.float32(0.0), np.float32(0.7385), np.float32(0.6666), np.float32(0.9487), np.float32(0.9623)] 
+2026-10-19 12:17:28.222549: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 12:17:28.511874: lr: 0.000684 
+2026-10-19 12:17:28.512233: This epoch took 248.427599 s
+ 
+2026-10-19 12:17:28.512441: 
+epoch:  344 
+2026-10-19 12:21:34.995251: train loss : -0.8248 
+2026-10-19 12:21:40.351040: validation loss: -0.7318 
+2026-10-19 12:21:40.352128: Average global foreground Dice: [np.float32(0.947), np.float32(0.7125), np.float32(0.8738), np.float32(0.8925), np.float32(0.7969), np.float32(0.9309), np.float32(0.8886), np.float32(0.6161), np.float32(0.0), np.float32(0.6482), np.float32(0.7668), np.float32(0.8441), np.float32(0.693), np.float32(0.58), np.float32(0.0081), np.float32(0.0), np.float32(0.8096), np.float32(0.6654), np.float32(0.8472), np.float32(0.7082), np.float32(0.2898), np.float32(0.7951), np.float32(0.9269), np.float32(0.9241), np.float32(0.6489), np.float32(0.6987), np.float32(0.4219), np.float32(0.8056), np.float32(0.6215), np.float32(0.6641), np.float32(0.0), np.float32(0.0), np.float32(0.7544), np.float32(0.6627), np.float32(0.9607), np.float32(0.9688)] 
+2026-10-19 12:21:40.352417: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 12:21:40.631519: lr: 0.000683 
+2026-10-19 12:21:40.631958: This epoch took 252.119397 s
+ 
+2026-10-19 12:21:40.632671: 
+epoch:  345 
+2026-10-19 12:26:01.488351: train loss : -0.8223 
+2026-10-19 12:26:06.841175: validation loss: -0.7217 
+2026-10-19 12:26:06.842279: Average global foreground Dice: [np.float32(0.9379), np.float32(0.7667), np.float32(0.8552), np.float32(0.8864), np.float32(0.7888), np.float32(0.9076), np.float32(0.8484), np.float32(0.7431), np.float32(0.0), np.float32(0.595), np.float32(0.7739), np.float32(0.8009), np.float32(0.7176), np.float32(0.6194), np.float32(0.0035), np.float32(0.0), np.float32(0.8174), np.float32(0.6662), np.float32(0.8346), np.float32(0.7202), np.float32(0.4988), np.float32(0.6721), np.float32(0.9296), np.float32(0.922), np.float32(0.6332), np.float32(0.6559), np.float32(0.429), np.float32(0.7697), np.float32(0.6774), np.float32(0.696), np.float32(0.0), np.float32(0.0), np.float32(0.7342), np.float32(0.6381), np.float32(0.959), np.float32(0.9672)] 
+2026-10-19 12:26:06.842528: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 12:26:07.132367: lr: 0.000682 
+2026-10-19 12:26:07.132619: This epoch took 266.499735 s
+ 
+2026-10-19 12:26:07.132700: 
+epoch:  346 
+2026-10-19 12:30:13.957411: train loss : -0.8270 
+2026-10-19 12:30:19.321723: validation loss: -0.7408 
+2026-10-19 12:30:19.322788: Average global foreground Dice: [np.float32(0.9424), np.float32(0.754), np.float32(0.8767), np.float32(0.8845), np.float32(0.8081), np.float32(0.9262), np.float32(0.8953), np.float32(0.7198), np.float32(0.0), np.float32(0.4904), np.float32(0.7596), np.float32(0.8328), np.float32(0.7236), np.float32(0.5799), np.float32(0.0), np.float32(0.0), np.float32(0.8249), np.float32(0.6659), np.float32(0.8418), np.float32(0.703), np.float32(0.4357), np.float32(0.7804), np.float32(0.9342), np.float32(0.9062), np.float32(0.6242), np.float32(0.6867), np.float32(0.4083), np.float32(0.8474), np.float32(0.6659), np.float32(0.7772), np.float32(0.0), np.float32(0.0), np.float32(0.7461), np.float32(0.6545), np.float32(0.9603), np.float32(0.9698)] 
+2026-10-19 12:30:19.322988: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 12:30:19.603650: lr: 0.000681 
+2026-10-19 12:30:19.603877: This epoch took 252.471122 s
+ 
+2026-10-19 12:30:19.604028: 
+epoch:  347 
+2026-10-19 12:34:23.197057: train loss : -0.8336 
+2026-10-19 12:34:28.551006: validation loss: -0.7379 
+2026-10-19 12:34:28.552068: Average global foreground Dice: [np.float32(0.9438), np.float32(0.7778), np.float32(0.867), np.float32(0.8871), np.float32(0.814), np.float32(0.9262), np.float32(0.8984), np.float32(0.7114), np.float32(0.0), np.float32(0.6205), np.float32(0.7563), np.float32(0.8198), np.float32(0.734), np.float32(0.6167), np.float32(0.0), np.float32(0.0), np.float32(0.8302), np.float32(0.6627), np.float32(0.8461), np.float32(0.7092), np.float32(0.4081), np.float32(0.774), np.float32(0.9352), np.float32(0.9202), np.float32(0.6543), np.float32(0.6653), np.float32(0.4337), np.float32(0.8419), np.float32(0.6708), np.float32(0.74), np.float32(0.0), np.float32(0.0), np.float32(0.7082), np.float32(0.6733), np.float32(0.9597), np.float32(0.9688)] 
+2026-10-19 12:34:28.552421: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 12:34:28.843058: lr: 0.00068 
+2026-10-19 12:34:28.843364: This epoch took 249.239012 s
+ 
+2026-10-19 12:34:28.843487: 
+epoch:  348 
+2026-10-19 12:38:53.000313: train loss : -0.8339 
+2026-10-19 12:38:58.342065: validation loss: -0.7323 
+2026-10-19 12:38:58.343278: Average global foreground Dice: [np.float32(0.9347), np.float32(0.7489), np.float32(0.8754), np.float32(0.8814), np.float32(0.7804), np.float32(0.9347), np.float32(0.8952), np.float32(0.6121), np.float32(0.0), np.float32(0.6234), np.float32(0.7535), np.float32(0.8271), np.float32(0.7038), np.float32(0.6152), np.float32(0.0), np.float32(0.0), np.float32(0.8222), np.float32(0.6577), np.float32(0.8418), np.float32(0.694), np.float32(0.389), np.float32(0.7548), np.float32(0.9206), np.float32(0.9194), np.float32(0.6569), np.float32(0.6815), np.float32(0.3756), np.float32(0.8502), np.float32(0.6383), np.float32(0.7265), np.float32(0.0), np.float32(0.0), np.float32(0.7388), np.float32(0.6561), np.float32(0.9589), np.float32(0.9673)] 
+2026-10-19 12:38:58.343717: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 12:38:58.631589: lr: 0.00068 
+2026-10-19 12:38:58.631938: This epoch took 269.788287 s
+ 
+2026-10-19 12:38:58.632048: 
+epoch:  349 
+2026-10-19 12:42:59.830709: train loss : -0.8326 
+2026-10-19 12:43:05.161386: validation loss: -0.7153 
+2026-10-19 12:43:05.162872: Average global foreground Dice: [np.float32(0.9348), np.float32(0.6831), np.float32(0.8596), np.float32(0.8763), np.float32(0.7688), np.float32(0.9314), np.float32(0.8784), np.float32(0.5584), np.float32(0.0), np.float32(0.6214), np.float32(0.7299), np.float32(0.8304), np.float32(0.6789), np.float32(0.6181), np.float32(0.0), np.float32(0.0), np.float32(0.8082), np.float32(0.651), np.float32(0.84), np.float32(0.6828), np.float32(0.3045), np.float32(0.7491), np.float32(0.9286), np.float32(0.9119), np.float32(0.6177), np.float32(0.658), np.float32(0.3725), np.float32(0.8695), np.float32(0.5653), np.float32(0.7066), np.float32(0.0), np.float32(0.0), np.float32(0.7195), np.float32(0.7), np.float32(0.9565), np.float32(0.9695)] 
+2026-10-19 12:43:05.163353: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 12:43:05.522408: lr: 0.000679 
+2026-10-19 12:43:05.522844: saving scheduled checkpoint file... 
+2026-10-19 12:43:05.531503: saving checkpoint... 
+2026-10-19 12:43:05.662565: done, saving took 0.14 seconds 
+2026-10-19 12:43:05.664185: done 
+2026-10-19 12:43:05.664422: This epoch took 247.032318 s
+ 
+2026-10-19 12:43:05.664507: 
+epoch:  350 
+2026-10-19 12:47:28.711485: train loss : -0.8188 
+2026-10-19 12:47:34.067090: validation loss: -0.7265 
+2026-10-19 12:47:34.068326: Average global foreground Dice: [np.float32(0.9431), np.float32(0.7207), np.float32(0.8713), np.float32(0.8838), np.float32(0.7976), np.float32(0.9297), np.float32(0.874), np.float32(0.6893), np.float32(0.0), np.float32(0.5558), np.float32(0.7517), np.float32(0.8415), np.float32(0.703), np.float32(0.5596), np.float32(0.0), np.float32(0.0), np.float32(0.81), np.float32(0.6623), np.float32(0.8221), np.float32(0.6995), np.float32(0.4184), np.float32(0.7578), np.float32(0.9303), np.float32(0.9146), np.float32(0.6353), np.float32(0.6847), np.float32(0.3401), np.float32(0.8878), np.float32(0.6202), np.float32(0.7302), np.float32(0.0), np.float32(0.0), np.float32(0.7153), np.float32(0.65), np.float32(0.9581), np.float32(0.9671)] 
+2026-10-19 12:47:34.068590: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 12:47:34.403492: lr: 0.000678 
+2026-10-19 12:47:34.403925: This epoch took 268.739359 s
+ 
+2026-10-19 12:47:34.404197: 
+epoch:  351 
+2026-10-19 12:51:26.077538: train loss : -0.8312 
+2026-10-19 12:51:31.443977: validation loss: -0.7298 
+2026-10-19 12:51:31.444894: Average global foreground Dice: [np.float32(0.9423), np.float32(0.7395), np.float32(0.8728), np.float32(0.8925), np.float32(0.8162), np.float32(0.9349), np.float32(0.8912), np.float32(0.7359), np.float32(0.0), np.float32(0.4999), np.float32(0.7551), np.float32(0.849), np.float32(0.6954), np.float32(0.6049), np.float32(0.0), np.float32(0.0), np.float32(0.824), np.float32(0.6653), np.float32(0.838), np.float32(0.7006), np.float32(0.3687), np.float32(0.7926), np.float32(0.9285), np.float32(0.9282), np.float32(0.644), np.float32(0.6667), np.float32(0.3607), np.float32(0.8687), np.float32(0.5885), np.float32(0.7408), np.float32(0.0), np.float32(0.0), np.float32(0.7197), np.float32(0.6525), np.float32(0.9603), np.float32(0.9696)] 
+2026-10-19 12:51:31.445134: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 12:51:31.748317: lr: 0.000677 
+2026-10-19 12:51:31.748864: This epoch took 237.344530 s
+ 
+2026-10-19 12:51:31.749178: 
+epoch:  352 
+2026-10-19 12:55:40.059951: train loss : -0.8298 
+2026-10-19 12:55:45.407933: validation loss: -0.7330 
+2026-10-19 12:55:45.408887: Average global foreground Dice: [np.float32(0.9455), np.float32(0.7747), np.float32(0.8698), np.float32(0.8827), np.float32(0.7949), np.float32(0.9354), np.float32(0.8787), np.float32(0.7676), np.float32(0.0), np.float32(0.5434), np.float32(0.7458), np.float32(0.8409), np.float32(0.7391), np.float32(0.6079), np.float32(0.0), np.float32(0.0), np.float32(0.8192), np.float32(0.6661), np.float32(0.8298), np.float32(0.6947), np.float32(0.4529), np.float32(0.7697), np.float32(0.9337), np.float32(0.9143), np.float32(0.6631), np.float32(0.6753), np.float32(0.3456), np.float32(0.8421), np.float32(0.4858), np.float32(0.7047), np.float32(0.0), np.float32(0.0), np.float32(0.7175), np.float32(0.6541), np.float32(0.9617), np.float32(0.9691)] 
+2026-10-19 12:55:45.409187: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 12:55:45.701221: lr: 0.000676 
+2026-10-19 12:55:45.701500: This epoch took 253.952091 s
+ 
+2026-10-19 12:55:45.701598: 
+epoch:  353 
+2026-10-19 12:59:46.335114: train loss : -0.8333 
+2026-10-19 12:59:51.694293: validation loss: -0.7313 
+2026-10-19 12:59:51.695240: Average global foreground Dice: [np.float32(0.9375), np.float32(0.7217), np.float32(0.872), np.float32(0.8785), np.float32(0.7599), np.float32(0.9354), np.float32(0.892), np.float32(0.4685), np.float32(0.0), np.float32(0.5536), np.float32(0.744), np.float32(0.8349), np.float32(0.715), np.float32(0.594), np.float32(0.0), np.float32(0.0), np.float32(0.8282), np.float32(0.6841), np.float32(0.8461), np.float32(0.7175), np.float32(0.322), np.float32(0.7584), np.float32(0.9263), np.float32(0.9246), np.float32(0.6498), np.float32(0.6938), np.float32(0.2674), np.float32(0.8512), np.float32(0.6069), np.float32(0.7651), np.float32(0.0), np.float32(0.0), np.float32(0.7016), np.float32(0.642), np.float32(0.9645), np.float32(0.9708)] 
+2026-10-19 12:59:51.695576: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 12:59:51.975015: lr: 0.000675 
+2026-10-19 12:59:51.975387: This epoch took 246.273717 s
+ 
+2026-10-19 12:59:51.976123: 
+epoch:  354 
+2026-10-19 13:04:19.343004: train loss : -0.8301 
+2026-10-19 13:04:24.689350: validation loss: -0.7207 
+2026-10-19 13:04:24.690307: Average global foreground Dice: [np.float32(0.9427), np.float32(0.7571), np.float32(0.8743), np.float32(0.8835), np.float32(0.796), np.float32(0.9313), np.float32(0.8914), np.float32(0.6396), np.float32(0.0), np.float32(0.5598), np.float32(0.7442), np.float32(0.82), np.float32(0.7211), np.float32(0.6145), np.float32(0.0), np.float32(0.0), np.float32(0.8172), np.float32(0.6599), np.float32(0.8341), np.float32(0.7059), np.float32(0.2967), np.float32(0.7505), np.float32(0.9269), np.float32(0.9071), np.float32(0.6273), np.float32(0.7002), np.float32(0.3644), np.float32(0.8764), np.float32(0.557), np.float32(0.7217), np.float32(0.0), np.float32(0.0), np.float32(0.7352), np.float32(0.6969), np.float32(0.9611), np.float32(0.9694)] 
+2026-10-19 13:04:24.690575: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 13:04:25.030598: lr: 0.000674 
+2026-10-19 13:04:25.031064: This epoch took 273.054752 s
+ 
+2026-10-19 13:04:25.031401: 
+epoch:  355 
+2026-10-19 13:08:09.122382: train loss : -0.8362 
+2026-10-19 13:08:14.472247: validation loss: -0.7440 
+2026-10-19 13:08:14.473392: Average global foreground Dice: [np.float32(0.9395), np.float32(0.7338), np.float32(0.8804), np.float32(0.8872), np.float32(0.7981), np.float32(0.9228), np.float32(0.9036), np.float32(0.5889), np.float32(0.0), np.float32(0.5297), np.float32(0.7473), np.float32(0.8402), np.float32(0.7332), np.float32(0.597), np.float32(0.0), np.float32(0.0), np.float32(0.8236), np.float32(0.6758), np.float32(0.8425), np.float32(0.7072), np.float32(0.27), np.float32(0.794), np.float32(0.9284), np.float32(0.9252), np.float32(0.6532), np.float32(0.6876), np.float32(0.3553), np.float32(0.8643), np.float32(0.6227), np.float32(0.8019), np.float32(0.0), np.float32(0.0), np.float32(0.7543), np.float32(0.6561), np.float32(0.964), np.float32(0.9689)] 
+2026-10-19 13:08:14.473769: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 13:08:14.809335: lr: 0.000673 
+2026-10-19 13:08:14.809715: This epoch took 229.778075 s
+ 
+2026-10-19 13:08:14.809931: 
+epoch:  356 
+2026-10-19 13:12:33.476893: train loss : -0.8263 
+2026-10-19 13:12:38.821159: validation loss: -0.7389 
+2026-10-19 13:12:38.822158: Average global foreground Dice: [np.float32(0.9435), np.float32(0.7449), np.float32(0.8661), np.float32(0.8879), np.float32(0.7862), np.float32(0.9381), np.float32(0.8976), np.float32(0.6742), np.float32(0.0), np.float32(0.4314), np.float32(0.7551), np.float32(0.8461), np.float32(0.702), np.float32(0.606), np.float32(0.0), np.float32(0.0), np.float32(0.835), np.float32(0.6828), np.float32(0.8494), np.float32(0.732), np.float32(0.3604), np.float32(0.7829), np.float32(0.932), np.float32(0.9276), np.float32(0.6701), np.float32(0.7002), np.float32(0.3669), np.float32(0.8496), np.float32(0.6385), np.float32(0.7938), np.float32(0.0), np.float32(0.0), np.float32(0.74), np.float32(0.6676), np.float32(0.9658), np.float32(0.9712)] 
+2026-10-19 13:12:38.822340: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 13:12:39.107664: lr: 0.000672 
+2026-10-19 13:12:39.108071: This epoch took 264.298045 s
+ 
+2026-10-19 13:12:39.108269: 
+epoch:  357 
+2026-10-19 13:16:37.817902: train loss : -0.8389 
+2026-10-19 13:16:43.158011: validation loss: -0.7260 
+2026-10-19 13:16:43.159176: Average global foreground Dice: [np.float32(0.9403), np.float32(0.7187), np.float32(0.8767), np.float32(0.8879), np.float32(0.7961), np.float32(0.9374), np.float32(0.897), np.float32(0.5746), np.float32(0.0), np.float32(0.4192), np.float32(0.7309), np.float32(0.8152), np.float32(0.7179), np.float32(0.5845), np.float32(0.0), np.float32(0.0), np.float32(0.8326), np.float32(0.67), np.float32(0.8506), np.float32(0.7396), np.float32(0.3147), np.float32(0.7516), np.float32(0.9309), np.float32(0.9232), np.float32(0.6568), np.float32(0.6935), np.float32(0.3208), np.float32(0.8666), np.float32(0.6023), np.float32(0.7441), np.float32(0.0), np.float32(0.0), np.float32(0.74), np.float32(0.6791), np.float32(0.9632), np.float32(0.9698)] 
+2026-10-19 13:16:43.159663: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 13:16:43.445927: lr: 0.000671 
+2026-10-19 13:16:43.446156: This epoch took 244.337784 s
+ 
+2026-10-19 13:16:43.446235: 
+epoch:  358 
+2026-10-19 13:20:58.892861: train loss : -0.8360 
+2026-10-19 13:21:04.232921: validation loss: -0.7308 
+2026-10-19 13:21:04.233910: Average global foreground Dice: [np.float32(0.9454), np.float32(0.7328), np.float32(0.8903), np.float32(0.8965), np.float32(0.8102), np.float32(0.9332), np.float32(0.8955), np.float32(0.6045), np.float32(0.0), np.float32(0.6113), np.float32(0.7411), np.float32(0.8241), np.float32(0.7004), np.float32(0.5544), np.float32(0.0), np.float32(0.0), np.float32(0.8269), np.float32(0.6565), np.float32(0.8419), np.float32(0.696), np.float32(0.2978), np.float32(0.8089), np.float32(0.929), np.float32(0.9289), np.float32(0.6384), np.float32(0.7019), np.float32(0.3644), np.float32(0.8447), np.float32(0.6477), np.float32(0.8064), np.float32(0.0), np.float32(0.0), np.float32(0.7029), np.float32(0.654), np.float32(0.9614), np.float32(0.969)] 
+2026-10-19 13:21:04.234273: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 13:21:04.534827: lr: 0.00067 
+2026-10-19 13:21:04.535175: This epoch took 261.088888 s
+ 
+2026-10-19 13:21:04.535450: 
+epoch:  359 
+2026-10-19 13:25:23.113554: train loss : -0.8273 
+2026-10-19 13:25:28.473387: validation loss: -0.7431 
+2026-10-19 13:25:28.474339: Average global foreground Dice: [np.float32(0.9443), np.float32(0.7854), np.float32(0.8819), np.float32(0.8716), np.float32(0.8094), np.float32(0.921), np.float32(0.8909), np.float32(0.5634), np.float32(0.0), np.float32(0.4991), np.float32(0.7456), np.float32(0.8334), np.float32(0.7446), np.float32(0.6293), np.float32(0.0), np.float32(0.0), np.float32(0.8305), np.float32(0.6573), np.float32(0.8408), np.float32(0.7094), np.float32(0.3504), np.float32(0.7707), np.float32(0.9314), np.float32(0.917), np.float32(0.6811), np.float32(0.6947), np.float32(0.3272), np.float32(0.8), np.float32(0.7112), np.float32(0.7745), np.float32(0.0), np.float32(0.0), np.float32(0.6832), np.float32(0.6825), np.float32(0.962), np.float32(0.9694)] 
+2026-10-19 13:25:28.474631: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 13:25:28.757566: lr: 0.000669 
+2026-10-19 13:25:28.757899: This epoch took 264.222330 s
+ 
+2026-10-19 13:25:28.758121: 
+epoch:  360 
+2026-10-19 13:29:51.197389: train loss : -0.8323 
+2026-10-19 13:29:56.545014: validation loss: -0.7296 
+2026-10-19 13:29:56.545939: Average global foreground Dice: [np.float32(0.9447), np.float32(0.7473), np.float32(0.8829), np.float32(0.8934), np.float32(0.7984), np.float32(0.9374), np.float32(0.892), np.float32(0.6826), np.float32(0.0), np.float32(0.5052), np.float32(0.7505), np.float32(0.8443), np.float32(0.7277), np.float32(0.6063), np.float32(0.0), np.float32(0.0), np.float32(0.8101), np.float32(0.6353), np.float32(0.8366), np.float32(0.7004), np.float32(0.2806), np.float32(0.7729), np.float32(0.9225), np.float32(0.9225), np.float32(0.6335), np.float32(0.6947), np.float32(0.3737), np.float32(0.8643), np.float32(0.608), np.float32(0.7605), np.float32(0.0), np.float32(0.0), np.float32(0.7074), np.float32(0.6429), np.float32(0.9605), np.float32(0.9693)] 
+2026-10-19 13:29:56.546091: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 13:29:56.846855: lr: 0.000668 
+2026-10-19 13:29:56.847108: This epoch took 268.088860 s
+ 
+2026-10-19 13:29:56.847316: 
+epoch:  361 
+2026-10-19 13:33:59.730010: train loss : -0.8316 
+2026-10-19 13:34:05.080972: validation loss: -0.7398 
+2026-10-19 13:34:05.082065: Average global foreground Dice: [np.float32(0.9468), np.float32(0.7666), np.float32(0.8661), np.float32(0.8878), np.float32(0.793), np.float32(0.934), np.float32(0.897), np.float32(0.6236), np.float32(0.0), np.float32(0.613), np.float32(0.7728), np.float32(0.8485), np.float32(0.7064), np.float32(0.6565), np.float32(0.0), np.float32(0.0), np.float32(0.8226), np.float32(0.6689), np.float32(0.8386), np.float32(0.7188), np.float32(0.3437), np.float32(0.781), np.float32(0.9176), np.float32(0.9087), np.float32(0.6578), np.float32(0.7027), np.float32(0.3235), np.float32(0.8575), np.float32(0.6202), np.float32(0.7591), np.float32(0.0), np.float32(0.0), np.float32(0.7461), np.float32(0.6671), np.float32(0.9303), np.float32(0.9643)] 
+2026-10-19 13:34:05.082422: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 13:34:05.367134: lr: 0.000667 
+2026-10-19 13:34:05.367413: This epoch took 248.519952 s
+ 
+2026-10-19 13:34:05.367505: 
+epoch:  362 
+2026-10-19 13:38:05.420502: train loss : -0.8324 
+2026-10-19 13:38:10.779316: validation loss: -0.7257 
+2026-10-19 13:38:10.780275: Average global foreground Dice: [np.float32(0.9483), np.float32(0.7394), np.float32(0.8776), np.float32(0.8915), np.float32(0.7676), np.float32(0.9353), np.float32(0.8957), np.float32(0.7094), np.float32(0.0), np.float32(0.5108), np.float32(0.7421), np.float32(0.8465), np.float32(0.6613), np.float32(0.6193), np.float32(0.0056), np.float32(0.0), np.float32(0.8375), np.float32(0.7023), np.float32(0.8512), np.float32(0.7318), np.float32(0.3919), np.float32(0.8032), np.float32(0.9238), np.float32(0.9129), np.float32(0.6273), np.float32(0.7256), np.float32(0.362), np.float32(0.8821), np.float32(0.5787), np.float32(0.7351), np.float32(0.0), np.float32(0.0), np.float32(0.7232), np.float32(0.6671), np.float32(0.9526), np.float32(0.9689)] 
+2026-10-19 13:38:10.780622: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 13:38:11.072072: lr: 0.000666 
+2026-10-19 13:38:11.072333: This epoch took 245.704765 s
+ 
+2026-10-19 13:38:11.072424: 
+epoch:  363 
+2026-10-19 13:42:41.378331: train loss : -0.8295 
+2026-10-19 13:42:46.750175: validation loss: -0.7444 
+2026-10-19 13:42:46.751321: Average global foreground Dice: [np.float32(0.9413), np.float32(0.759), np.float32(0.873), np.float32(0.8837), np.float32(0.8073), np.float32(0.9355), np.float32(0.9015), np.float32(0.4439), np.float32(0.0), np.float32(0.5516), np.float32(0.7513), np.float32(0.8354), np.float32(0.7299), np.float32(0.6516), np.float32(0.0), np.float32(0.0), np.float32(0.8272), np.float32(0.6688), np.float32(0.8339), np.float32(0.7031), np.float32(0.421), np.float32(0.7946), np.float32(0.9125), np.float32(0.9061), np.float32(0.6246), np.float32(0.6781), np.float32(0.4379), np.float32(0.6522), np.float32(0.6574), np.float32(0.742), np.float32(0.0), np.float32(0.0), np.float32(0.7019), np.float32(0.6402), np.float32(0.9493), np.float32(0.9684)] 
+2026-10-19 13:42:46.751555: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 13:42:47.029213: lr: 0.000665 
+2026-10-19 13:42:47.029673: This epoch took 275.957170 s
+ 
+2026-10-19 13:42:47.029873: 
+epoch:  364 
+2026-10-19 13:46:57.660217: train loss : -0.8341 
+2026-10-19 13:47:03.005721: validation loss: -0.7437 
+2026-10-19 13:47:03.006503: Average global foreground Dice: [np.float32(0.9433), np.float32(0.7701), np.float32(0.8826), np.float32(0.8857), np.float32(0.7907), np.float32(0.9329), np.float32(0.893), np.float32(0.6058), np.float32(0.0), np.float32(0.5844), np.float32(0.7401), np.float32(0.8105), np.float32(0.7178), np.float32(0.6086), np.float32(0.0), np.float32(0.0), np.float32(0.8313), np.float32(0.67), np.float32(0.8373), np.float32(0.7133), np.float32(0.3614), np.float32(0.8115), np.float32(0.9332), np.float32(0.9247), np.float32(0.7058), np.float32(0.7206), np.float32(0.3966), np.float32(0.8555), np.float32(0.6809), np.float32(0.7867), np.float32(0.0), np.float32(0.0), np.float32(0.7653), np.float32(0.6723), np.float32(0.9549), np.float32(0.9673)] 
+2026-10-19 13:47:03.006742: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 13:47:03.289901: lr: 0.000665 
+2026-10-19 13:47:03.290153: This epoch took 256.260194 s
+ 
+2026-10-19 13:47:03.290231: 
+epoch:  365 
+2026-10-19 13:51:19.597354: train loss : -0.8261 
+2026-10-19 13:51:24.937127: validation loss: -0.7189 
+2026-10-19 13:51:24.938079: Average global foreground Dice: [np.float32(0.9422), np.float32(0.7114), np.float32(0.8635), np.float32(0.89), np.float32(0.7332), np.float32(0.9414), np.float32(0.8965), np.float32(0.706), np.float32(0.0), np.float32(0.4029), np.float32(0.7501), np.float32(0.8298), np.float32(0.7047), np.float32(0.633), np.float32(0.0), np.float32(0.0), np.float32(0.8162), np.float32(0.4277), np.float32(0.8374), np.float32(0.6727), np.float32(0.366), np.float32(0.7741), np.float32(0.9179), np.float32(0.9145), np.float32(0.6524), np.float32(0.6725), np.float32(0.3582), np.float32(0.8699), np.float32(0.6136), np.float32(0.7527), np.float32(0.0), np.float32(0.0), np.float32(0.7508), np.float32(0.6604), np.float32(0.9556), np.float32(0.9668)] 
+2026-10-19 13:51:24.938327: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 13:51:25.260861: lr: 0.000664 
+2026-10-19 13:51:25.261465: This epoch took 261.970946 s
+ 
+2026-10-19 13:51:25.261617: 
+epoch:  366 
+2026-10-19 13:55:45.283646: train loss : -0.8343 
+2026-10-19 13:55:50.631597: validation loss: -0.7353 
+2026-10-19 13:55:50.632553: Average global foreground Dice: [np.float32(0.9432), np.float32(0.7478), np.float32(0.8899), np.float32(0.8917), np.float32(0.791), np.float32(0.9254), np.float32(0.8888), np.float32(0.4892), np.float32(0.0), np.float32(0.6001), np.float32(0.7445), np.float32(0.834), np.float32(0.6754), np.float32(0.5384), np.float32(0.0), np.float32(0.0), np.float32(0.8214), np.float32(0.6647), np.float32(0.8502), np.float32(0.7245), np.float32(0.3179), np.float32(0.8021), np.float32(0.9308), np.float32(0.9376), np.float32(0.6735), np.float32(0.7025), np.float32(0.3151), np.float32(0.8443), np.float32(0.6116), np.float32(0.8231), np.float32(0.0), np.float32(0.0), np.float32(0.7499), np.float32(0.6572), np.float32(0.9529), np.float32(0.9692)] 
+2026-10-19 13:55:50.632857: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 13:55:50.913957: lr: 0.000663 
+2026-10-19 13:55:50.914401: This epoch took 265.652710 s
+ 
+2026-10-19 13:55:50.914604: 
+epoch:  367 
+2026-10-19 13:59:56.683297: train loss : -0.8299 
+2026-10-19 14:00:02.032378: validation loss: -0.7172 
+2026-10-19 14:00:02.033601: Average global foreground Dice: [np.float32(0.9358), np.float32(0.7475), np.float32(0.8799), np.float32(0.8917), np.float32(0.7945), np.float32(0.9137), np.float32(0.8928), np.float32(0.5128), np.float32(0.0), np.float32(0.3602), np.float32(0.7273), np.float32(0.7742), np.float32(0.6848), np.float32(0.6185), np.float32(0.0), np.float32(0.0), np.float32(0.8256), np.float32(0.6483), np.float32(0.8458), np.float32(0.7069), np.float32(0.3167), np.float32(0.784), np.float32(0.9331), np.float32(0.9345), np.float32(0.6617), np.float32(0.7234), np.float32(0.2967), np.float32(0.8704), np.float32(0.544), np.float32(0.7775), np.float32(0.0), np.float32(0.0), np.float32(0.7435), np.float32(0.702), np.float32(0.9527), np.float32(0.966)] 
+2026-10-19 14:00:02.034000: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 14:00:02.326094: lr: 0.000662 
+2026-10-19 14:00:02.326518: This epoch took 251.411808 s
+ 
+2026-10-19 14:00:02.326842: 
+epoch:  368 
+2026-10-19 14:04:32.431630: train loss : -0.8240 
+2026-10-19 14:04:37.774382: validation loss: -0.7348 
+2026-10-19 14:04:37.775695: Average global foreground Dice: [np.float32(0.941), np.float32(0.7837), np.float32(0.8811), np.float32(0.8937), np.float32(0.8249), np.float32(0.9234), np.float32(0.8943), np.float32(0.5278), np.float32(0.0), np.float32(0.4426), np.float32(0.7457), np.float32(0.8246), np.float32(0.693), np.float32(0.617), np.float32(0.0), np.float32(0.0), np.float32(0.8277), np.float32(0.6563), np.float32(0.8437), np.float32(0.6982), np.float32(0.3518), np.float32(0.8118), np.float32(0.9238), np.float32(0.9302), np.float32(0.6463), np.float32(0.6912), np.float32(0.3647), np.float32(0.7743), np.float32(0.6506), np.float32(0.7839), np.float32(0.0), np.float32(0.0), np.float32(0.7334), np.float32(0.6901), np.float32(0.9599), np.float32(0.9678)] 
+2026-10-19 14:04:37.775941: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 14:04:38.095003: lr: 0.000661 
+2026-10-19 14:04:38.095428: This epoch took 275.768415 s
+ 
+2026-10-19 14:04:38.095825: 
+epoch:  369 
+2026-10-19 14:08:52.090377: train loss : -0.8262 
+2026-10-19 14:08:57.431692: validation loss: -0.7313 
+2026-10-19 14:08:57.432578: Average global foreground Dice: [np.float32(0.9422), np.float32(0.7269), np.float32(0.8737), np.float32(0.8985), np.float32(0.7853), np.float32(0.929), np.float32(0.8896), np.float32(0.6067), np.float32(0.0), np.float32(0.1885), np.float32(0.7406), np.float32(0.8293), np.float32(0.6796), np.float32(0.6138), np.float32(0.0), np.float32(0.0), np.float32(0.8192), np.float32(0.6619), np.float32(0.8489), np.float32(0.7248), np.float32(0.371), np.float32(0.7958), np.float32(0.928), np.float32(0.9265), np.float32(0.673), np.float32(0.7341), np.float32(0.3747), np.float32(0.8565), np.float32(0.632), np.float32(0.7897), np.float32(0.0), np.float32(0.0), np.float32(0.7616), np.float32(0.6921), np.float32(0.9573), np.float32(0.9679)] 
+2026-10-19 14:08:57.432733: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 14:08:57.714289: lr: 0.00066 
+2026-10-19 14:08:57.714585: This epoch took 259.618380 s
+ 
+2026-10-19 14:08:57.714675: 
+epoch:  370 
+2026-10-19 14:12:12.212181: train loss : -0.8358 
+2026-10-19 14:12:17.563911: validation loss: -0.7474 
+2026-10-19 14:12:17.564959: Average global foreground Dice: [np.float32(0.9403), np.float32(0.7612), np.float32(0.8747), np.float32(0.8824), np.float32(0.8099), np.float32(0.9352), np.float32(0.8936), np.float32(0.5612), np.float32(0.0), np.float32(0.3908), np.float32(0.7375), np.float32(0.8223), np.float32(0.7557), np.float32(0.6577), np.float32(0.0), np.float32(0.0), np.float32(0.8179), np.float32(0.6452), np.float32(0.8347), np.float32(0.6922), np.float32(0.3165), np.float32(0.7651), np.float32(0.9339), np.float32(0.9284), np.float32(0.6435), np.float32(0.6719), np.float32(0.3546), np.float32(0.8569), np.float32(0.6705), np.float32(0.7903), np.float32(0.0), np.float32(0.0), np.float32(0.7234), np.float32(0.6758), np.float32(0.9586), np.float32(0.9692)] 
+2026-10-19 14:12:17.565221: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 14:12:17.858912: lr: 0.000659 
+2026-10-19 14:12:17.859165: This epoch took 200.144423 s
+ 
+2026-10-19 14:12:17.859269: 
+epoch:  371 
+2026-10-19 14:15:54.844715: train loss : -0.8401 
+2026-10-19 14:16:00.211152: validation loss: -0.7454 
+2026-10-19 14:16:00.212273: Average global foreground Dice: [np.float32(0.9396), np.float32(0.7667), np.float32(0.8637), np.float32(0.8906), np.float32(0.8094), np.float32(0.9264), np.float32(0.8971), np.float32(0.6394), np.float32(0.0), np.float32(0.5058), np.float32(0.7479), np.float32(0.8316), np.float32(0.7481), np.float32(0.7168), np.float32(0.0), np.float32(0.0), np.float32(0.8301), np.float32(0.642), np.float32(0.8443), np.float32(0.7226), np.float32(0.372), np.float32(0.7867), np.float32(0.9202), np.float32(0.9242), np.float32(0.6221), np.float32(0.6861), np.float32(0.2698), np.float32(0.7892), np.float32(0.6139), np.float32(0.7916), np.float32(0.0), np.float32(0.0), np.float32(0.741), np.float32(0.6675), np.float32(0.9545), np.float32(0.963)] 
+2026-10-19 14:16:00.212884: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 14:16:00.536751: lr: 0.000658 
+2026-10-19 14:16:00.536982: This epoch took 222.677488 s
+ 
+2026-10-19 14:16:00.537065: 
+epoch:  372 
+2026-10-19 14:20:05.309417: train loss : -0.8286 
+2026-10-19 14:20:10.673847: validation loss: -0.7295 
+2026-10-19 14:20:10.674723: Average global foreground Dice: [np.float32(0.9374), np.float32(0.7461), np.float32(0.8559), np.float32(0.8838), np.float32(0.774), np.float32(0.9332), np.float32(0.8992), np.float32(0.7192), np.float32(0.0), np.float32(0.4581), np.float32(0.7466), np.float32(0.8189), np.float32(0.7214), np.float32(0.691), np.float32(0.0), np.float32(0.0), np.float32(0.8143), np.float32(0.6233), np.float32(0.8354), np.float32(0.7049), np.float32(0.3605), np.float32(0.776), np.float32(0.9178), np.float32(0.8987), np.float32(0.6059), np.float32(0.6606), np.float32(0.3691), np.float32(0.7379), np.float32(0.6229), np.float32(0.7725), np.float32(0.0), np.float32(0.0), np.float32(0.723), np.float32(0.6297), np.float32(0.9545), np.float32(0.9686)] 
+2026-10-19 14:20:10.674892: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 14:20:10.992880: lr: 0.000657 
+2026-10-19 14:20:10.993233: This epoch took 250.456110 s
+ 
+2026-10-19 14:20:10.993466: 
+epoch:  373 
+2026-10-19 14:24:02.275855: train loss : -0.8243 
+2026-10-19 14:24:07.603318: validation loss: -0.7294 
+2026-10-19 14:24:07.604333: Average global foreground Dice: [np.float32(0.9433), np.float32(0.7518), np.float32(0.8651), np.float32(0.8803), np.float32(0.7929), np.float32(0.9213), np.float32(0.8924), np.float32(0.7653), np.float32(0.0), np.float32(0.5008), np.float32(0.766), np.float32(0.8505), np.float32(0.7217), np.float32(0.6772), np.float32(0.0), np.float32(0.0), np.float32(0.8264), np.float32(0.6451), np.float32(0.8393), np.float32(0.7179), np.float32(0.3279), np.float32(0.7805), np.float32(0.9135), np.float32(0.9078), np.float32(0.5981), np.float32(0.7041), np.float32(0.3509), np.float32(0.7767), np.float32(0.5848), np.float32(0.7016), np.float32(0.0), np.float32(0.0), np.float32(0.7527), np.float32(0.6684), np.float32(0.957), np.float32(0.967)] 
+2026-10-19 14:24:07.604499: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 14:24:07.891563: lr: 0.000656 
+2026-10-19 14:24:07.891798: This epoch took 236.898239 s
+ 
+2026-10-19 14:24:07.891879: 
+epoch:  374 
+2026-10-19 14:28:27.003802: train loss : -0.8293 
+2026-10-19 14:28:32.355450: validation loss: -0.7429 
+2026-10-19 14:28:32.356654: Average global foreground Dice: [np.float32(0.9492), np.float32(0.7616), np.float32(0.8827), np.float32(0.8977), np.float32(0.8218), np.float32(0.9247), np.float32(0.8918), np.float32(0.8245), np.float32(0.0), np.float32(0.6009), np.float32(0.7623), np.float32(0.8508), np.float32(0.7353), np.float32(0.6265), np.float32(0.0), np.float32(0.0), np.float32(0.8306), np.float32(0.6765), np.float32(0.8439), np.float32(0.7045), np.float32(0.3494), np.float32(0.7912), np.float32(0.9365), np.float32(0.9302), np.float32(0.6192), np.float32(0.6856), np.float32(0.3426), np.float32(0.773), np.float32(0.6743), np.float32(0.785), np.float32(0.0), np.float32(0.0), np.float32(0.7465), np.float32(0.6629), np.float32(0.9564), np.float32(0.9704)] 
+2026-10-19 14:28:32.357112: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 14:28:32.646103: lr: 0.000655 
+2026-10-19 14:28:32.646607: This epoch took 264.754671 s
+ 
+2026-10-19 14:28:32.646810: 
+epoch:  375 
+2026-10-19 14:33:01.057324: train loss : -0.8352 
+2026-10-19 14:33:06.405294: validation loss: -0.7367 
+2026-10-19 14:33:06.406202: Average global foreground Dice: [np.float32(0.9433), np.float32(0.7606), np.float32(0.8632), np.float32(0.8973), np.float32(0.8152), np.float32(0.927), np.float32(0.8995), np.float32(0.7231), np.float32(0.0), np.float32(0.5127), np.float32(0.7582), np.float32(0.8424), np.float32(0.7473), np.float32(0.6263), np.float32(0.0), np.float32(0.0), np.float32(0.8331), np.float32(0.6598), np.float32(0.8421), np.float32(0.7202), np.float32(0.5203), np.float32(0.7637), np.float32(0.9319), np.float32(0.9197), np.float32(0.6592), np.float32(0.7048), np.float32(0.4508), np.float32(0.8132), np.float32(0.709), np.float32(0.7614), np.float32(0.0), np.float32(0.0), np.float32(0.7497), np.float32(0.6717), np.float32(0.9603), np.float32(0.9694)] 
+2026-10-19 14:33:06.406435: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 14:33:06.706416: lr: 0.000654 
+2026-10-19 14:33:06.706928: This epoch took 274.060037 s
+ 
+2026-10-19 14:33:06.707242: 
+epoch:  376 
+2026-10-19 14:37:09.836798: train loss : -0.8309 
+2026-10-19 14:37:15.191514: validation loss: -0.7295 
+2026-10-19 14:37:15.192567: Average global foreground Dice: [np.float32(0.943), np.float32(0.7348), np.float32(0.8631), np.float32(0.8821), np.float32(0.8127), np.float32(0.9331), np.float32(0.8922), np.float32(0.6323), np.float32(0.0), np.float32(0.5781), np.float32(0.7502), np.float32(0.8311), np.float32(0.702), np.float32(0.6869), np.float32(0.0), np.float32(0.0), np.float32(0.8216), np.float32(0.6725), np.float32(0.8427), np.float32(0.7271), np.float32(0.3445), np.float32(0.7695), np.float32(0.928), np.float32(0.9135), np.float32(0.6546), np.float32(0.7103), np.float32(0.2745), np.float32(0.8515), np.float32(0.6435), np.float32(0.7605), np.float32(0.0), np.float32(0.0), np.float32(0.6737), np.float32(0.6464), np.float32(0.9468), np.float32(0.9655)] 
+2026-10-19 14:37:15.192984: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 14:37:15.472132: lr: 0.000653 
+2026-10-19 14:37:15.472423: This epoch took 248.764945 s
+ 
+2026-10-19 14:37:15.472528: 
+epoch:  377 
+2026-10-19 14:41:09.204229: train loss : -0.8372 
+2026-10-19 14:41:14.560304: validation loss: -0.7521 
+2026-10-19 14:41:14.561473: Average global foreground Dice: [np.float32(0.9323), np.float32(0.7728), np.float32(0.8679), np.float32(0.8918), np.float32(0.821), np.float32(0.9277), np.float32(0.8953), np.float32(0.6842), np.float32(0.0), np.float32(0.6023), np.float32(0.7639), np.float32(0.8247), np.float32(0.7448), np.float32(0.6757), np.float32(0.0), np.float32(0.0), np.float32(0.8247), np.float32(0.6567), np.float32(0.8388), np.float32(0.7093), np.float32(0.3731), np.float32(0.7887), np.float32(0.925), np.float32(0.9237), np.float32(0.6532), np.float32(0.67), np.float32(0.3087), np.float32(0.8089), np.float32(0.6266), np.float32(0.7934), np.float32(0.0), np.float32(0.0), np.float32(0.7213), np.float32(0.6441), np.float32(0.9438), np.float32(0.9654)] 
+2026-10-19 14:41:14.561663: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 14:41:14.874908: lr: 0.000652 
+2026-10-19 14:41:14.875433: This epoch took 239.402801 s
+ 
+2026-10-19 14:41:14.875590: 
+epoch:  378 
+2026-10-19 14:45:24.901268: train loss : -0.8272 
+2026-10-19 14:45:30.254856: validation loss: -0.7408 
+2026-10-19 14:45:30.255869: Average global foreground Dice: [np.float32(0.9351), np.float32(0.7619), np.float32(0.8658), np.float32(0.8885), np.float32(0.8104), np.float32(0.9213), np.float32(0.9026), np.float32(0.7616), np.float32(0.0), np.float32(0.5988), np.float32(0.759), np.float32(0.8488), np.float32(0.6995), np.float32(0.6348), np.float32(0.0), np.float32(0.0), np.float32(0.834), np.float32(0.668), np.float32(0.8459), np.float32(0.7235), np.float32(0.3556), np.float32(0.7866), np.float32(0.9298), np.float32(0.9232), np.float32(0.6471), np.float32(0.6873), np.float32(0.2509), np.float32(0.8741), np.float32(0.64), np.float32(0.7633), np.float32(0.0), np.float32(0.0), np.float32(0.7392), np.float32(0.6484), np.float32(0.9552), np.float32(0.9652)] 
+2026-10-19 14:45:30.256030: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 14:45:30.595670: lr: 0.000651 
+2026-10-19 14:45:30.596288: This epoch took 255.720598 s
+ 
+2026-10-19 14:45:30.596669: 
+epoch:  379 
+2026-10-19 14:49:43.673301: train loss : -0.8286 
+2026-10-19 14:49:49.016445: validation loss: -0.7264 
+2026-10-19 14:49:49.017467: Average global foreground Dice: [np.float32(0.9276), np.float32(0.6948), np.float32(0.8729), np.float32(0.8883), np.float32(0.7954), np.float32(0.922), np.float32(0.8723), np.float32(0.7094), np.float32(0.0), np.float32(0.6196), np.float32(0.7365), np.float32(0.8087), np.float32(0.6145), np.float32(0.5918), np.float32(0.0), np.float32(0.0), np.float32(0.8009), np.float32(0.6612), np.float32(0.8453), np.float32(0.7007), np.float32(0.2735), np.float32(0.7866), np.float32(0.9202), np.float32(0.9089), np.float32(0.6257), np.float32(0.6941), np.float32(0.2335), np.float32(0.8745), np.float32(0.5067), np.float32(0.746), np.float32(0.0), np.float32(0.0), np.float32(0.7273), np.float32(0.6736), np.float32(0.9474), np.float32(0.9632)] 
+2026-10-19 14:49:49.017635: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 14:49:49.327132: lr: 0.00065 
+2026-10-19 14:49:49.327373: This epoch took 258.730333 s
+ 
+2026-10-19 14:49:49.327471: 
+epoch:  380 
+2026-10-19 14:54:35.106410: train loss : -0.8231 
+2026-10-19 14:54:40.467878: validation loss: -0.7454 
+2026-10-19 14:54:40.468742: Average global foreground Dice: [np.float32(0.9288), np.float32(0.7685), np.float32(0.8556), np.float32(0.8847), np.float32(0.8222), np.float32(0.9283), np.float32(0.8948), np.float32(0.7299), np.float32(0.0), np.float32(0.5249), np.float32(0.7534), np.float32(0.827), np.float32(0.7455), np.float32(0.6592), np.float32(0.0), np.float32(0.0), np.float32(0.8261), np.float32(0.6418), np.float32(0.8374), np.float32(0.6871), np.float32(0.3421), np.float32(0.7933), np.float32(0.9236), np.float32(0.9209), np.float32(0.6157), np.float32(0.6762), np.float32(0.3273), np.float32(0.8726), np.float32(0.6546), np.float32(0.7353), np.float32(0.0), np.float32(0.0), np.float32(0.7401), np.float32(0.6263), np.float32(0.9557), np.float32(0.9636)] 
+2026-10-19 14:54:40.468911: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 14:54:40.757827: lr: 0.000649 
+2026-10-19 14:54:40.758089: This epoch took 291.430546 s
+ 
+2026-10-19 14:54:40.758286: 
+epoch:  381 
+2026-10-19 14:58:52.940706: train loss : -0.8376 
+2026-10-19 14:58:58.284134: validation loss: -0.7485 
+2026-10-19 14:58:58.285084: Average global foreground Dice: [np.float32(0.9417), np.float32(0.7722), np.float32(0.8637), np.float32(0.9017), np.float32(0.7956), np.float32(0.9319), np.float32(0.8931), np.float32(0.7284), np.float32(0.0), np.float32(0.5839), np.float32(0.7678), np.float32(0.8187), np.float32(0.7255), np.float32(0.6637), np.float32(0.0), np.float32(0.0), np.float32(0.8318), np.float32(0.6683), np.float32(0.8439), np.float32(0.7384), np.float32(0.3987), np.float32(0.7486), np.float32(0.9315), np.float32(0.9168), np.float32(0.6304), np.float32(0.6712), np.float32(0.4113), np.float32(0.8659), np.float32(0.6821), np.float32(0.7363), np.float32(0.0), np.float32(0.0), np.float32(0.7493), np.float32(0.594), np.float32(0.9616), np.float32(0.9693)] 
+2026-10-19 14:58:58.285360: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 14:58:58.570166: lr: 0.000648 
+2026-10-19 14:58:58.570505: This epoch took 257.812134 s
+ 
+2026-10-19 14:58:58.570758: 
+epoch:  382 
+2026-10-19 15:02:59.818193: train loss : -0.8397 
+2026-10-19 15:03:05.161921: validation loss: -0.7420 
+2026-10-19 15:03:05.163107: Average global foreground Dice: [np.float32(0.9411), np.float32(0.7386), np.float32(0.8739), np.float32(0.8947), np.float32(0.8153), np.float32(0.9351), np.float32(0.882), np.float32(0.6161), np.float32(0.0), np.float32(0.5802), np.float32(0.7721), np.float32(0.8319), np.float32(0.7287), np.float32(0.6446), np.float32(0.0), np.float32(0.0), np.float32(0.8169), np.float32(0.6686), np.float32(0.8408), np.float32(0.709), np.float32(0.4236), np.float32(0.7646), np.float32(0.934), np.float32(0.9062), np.float32(0.6451), np.float32(0.6776), np.float32(0.4058), np.float32(0.841), np.float32(0.6559), np.float32(0.7423), np.float32(0.0), np.float32(0.0), np.float32(0.7583), np.float32(0.6657), np.float32(0.9566), np.float32(0.9654)] 
+2026-10-19 15:03:05.163472: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 15:03:05.467051: lr: 0.000648 
+2026-10-19 15:03:05.467499: This epoch took 246.896653 s
+ 
+2026-10-19 15:03:05.467645: 
+epoch:  383 
+2026-10-19 15:07:26.351139: train loss : -0.8280 
+2026-10-19 15:07:31.694333: validation loss: -0.7200 
+2026-10-19 15:07:31.695559: Average global foreground Dice: [np.float32(0.9404), np.float32(0.729), np.float32(0.8676), np.float32(0.9046), np.float32(0.816), np.float32(0.9379), np.float32(0.8864), np.float32(0.6359), np.float32(0.0), np.float32(0.3509), np.float32(0.7475), np.float32(0.8093), np.float32(0.693), np.float32(0.5932), np.float32(0.0038), np.float32(0.0), np.float32(0.8259), np.float32(0.6589), np.float32(0.8433), np.float32(0.7421), np.float32(0.3358), np.float32(0.768), np.float32(0.9277), np.float32(0.9275), np.float32(0.6166), np.float32(0.6965), np.float32(0.357), np.float32(0.8769), np.float32(0.5829), np.float32(0.7601), np.float32(0.0), np.float32(0.0), np.float32(0.7222), np.float32(0.508), np.float32(0.96), np.float32(0.97)] 
+2026-10-19 15:07:31.695979: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 15:07:31.986081: lr: 0.000647 
+2026-10-19 15:07:31.986336: This epoch took 266.518518 s
+ 
+2026-10-19 15:07:31.986421: 
+epoch:  384 
+2026-10-19 15:11:35.910055: train loss : -0.8341 
+2026-10-19 15:11:41.251245: validation loss: -0.7395 
+2026-10-19 15:11:41.252543: Average global foreground Dice: [np.float32(0.9363), np.float32(0.766), np.float32(0.8524), np.float32(0.8878), np.float32(0.7987), np.float32(0.9352), np.float32(0.8949), np.float32(0.6917), np.float32(0.0), np.float32(0.4896), np.float32(0.7735), np.float32(0.8231), np.float32(0.7567), np.float32(0.6716), np.float32(0.0), np.float32(0.0), np.float32(0.814), np.float32(0.6545), np.float32(0.8334), np.float32(0.6941), np.float32(0.3554), np.float32(0.7652), np.float32(0.9243), np.float32(0.924), np.float32(0.6292), np.float32(0.6844), np.float32(0.341), np.float32(0.8274), np.float32(0.6654), np.float32(0.7733), np.float32(0.0), np.float32(0.0), np.float32(0.7272), np.float32(0.6434), np.float32(0.9524), np.float32(0.9684)] 
+2026-10-19 15:11:41.252788: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 15:11:41.543018: lr: 0.000646 
+2026-10-19 15:11:41.543370: This epoch took 249.556886 s
+ 
+2026-10-19 15:11:41.543645: 
+epoch:  385 
+2026-10-19 15:15:45.820724: train loss : -0.8357 
+2026-10-19 15:15:51.179101: validation loss: -0.7317 
+2026-10-19 15:15:51.180331: Average global foreground Dice: [np.float32(0.9402), np.float32(0.711), np.float32(0.8739), np.float32(0.8905), np.float32(0.8052), np.float32(0.938), np.float32(0.8937), np.float32(0.5256), np.float32(0.0), np.float32(0.6111), np.float32(0.7696), np.float32(0.8508), np.float32(0.6968), np.float32(0.6361), np.float32(0.0007), np.float32(0.0), np.float32(0.8179), np.float32(0.6512), np.float32(0.8436), np.float32(0.7109), np.float32(0.226), np.float32(0.7732), np.float32(0.9317), np.float32(0.9226), np.float32(0.6457), np.float32(0.6862), np.float32(0.3828), np.float32(0.8075), np.float32(0.5688), np.float32(0.7646), np.float32(0.0), np.float32(0.0), np.float32(0.7462), np.float32(0.6562), np.float32(0.9604), np.float32(0.9688)] 
+2026-10-19 15:15:51.180691: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 15:15:51.737443: lr: 0.000645 
+2026-10-19 15:15:51.737715: This epoch took 250.193851 s
+ 
+2026-10-19 15:15:51.737841: 
+epoch:  386 
+2026-10-19 15:20:34.034057: train loss : -0.8303 
+2026-10-19 15:20:39.394114: validation loss: -0.7436 
+2026-10-19 15:20:39.394984: Average global foreground Dice: [np.float32(0.9404), np.float32(0.754), np.float32(0.8655), np.float32(0.9021), np.float32(0.8201), np.float32(0.921), np.float32(0.8952), np.float32(0.5676), np.float32(0.0), np.float32(0.4649), np.float32(0.77), np.float32(0.8361), np.float32(0.7041), np.float32(0.6284), np.float32(0.0), np.float32(0.0), np.float32(0.8214), np.float32(0.6543), np.float32(0.8367), np.float32(0.6908), np.float32(0.4363), np.float32(0.7702), np.float32(0.9343), np.float32(0.9175), np.float32(0.6494), np.float32(0.6732), np.float32(0.3989), np.float32(0.8356), np.float32(0.6864), np.float32(0.7427), np.float32(0.0), np.float32(0.0), np.float32(0.7053), np.float32(0.6624), np.float32(0.9614), np.float32(0.9668)] 
+2026-10-19 15:20:39.395149: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 15:20:39.685265: lr: 0.000644 
+2026-10-19 15:20:39.685513: This epoch took 287.947580 s
+ 
+2026-10-19 15:20:39.685590: 
+epoch:  387 
+2026-10-19 15:24:32.141523: train loss : -0.8282 
+2026-10-19 15:24:37.493634: validation loss: -0.7207 
+2026-10-19 15:24:37.494673: Average global foreground Dice: [np.float32(0.9383), np.float32(0.7409), np.float32(0.8716), np.float32(0.8916), np.float32(0.8125), np.float32(0.9282), np.float32(0.8835), np.float32(0.6448), np.float32(0.0), np.float32(0.5573), np.float32(0.7572), np.float32(0.8057), np.float32(0.7177), np.float32(0.6931), np.float32(0.0), np.float32(0.0), np.float32(0.8201), np.float32(0.6548), np.float32(0.8459), np.float32(0.7123), np.float32(0.3068), np.float32(0.7847), np.float32(0.9314), np.float32(0.9122), np.float32(0.6529), np.float32(0.6823), np.float32(0.3368), np.float32(0.8655), np.float32(0.492), np.float32(0.7548), np.float32(0.0), np.float32(0.0), np.float32(0.7242), np.float32(0.6921), np.float32(0.9604), np.float32(0.9693)] 
+2026-10-19 15:24:37.494855: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 15:24:37.789445: lr: 0.000643 
+2026-10-19 15:24:37.789903: This epoch took 238.104260 s
+ 
+2026-10-19 15:24:37.790232: 
+epoch:  388 
+2026-10-19 15:28:53.726002: train loss : -0.8284 
+2026-10-19 15:28:59.089848: validation loss: -0.7317 
+2026-10-19 15:28:59.090935: Average global foreground Dice: [np.float32(0.9271), np.float32(0.7102), np.float32(0.856), np.float32(0.8909), np.float32(0.7925), np.float32(0.9253), np.float32(0.8892), np.float32(0.6173), np.float32(0.0), np.float32(0.5758), np.float32(0.7654), np.float32(0.8464), np.float32(0.6456), np.float32(0.6063), np.float32(0.0), np.float32(0.0), np.float32(0.8267), np.float32(0.6677), np.float32(0.8401), np.float32(0.7065), np.float32(0.2846), np.float32(0.7777), np.float32(0.9282), np.float32(0.9108), np.float32(0.6256), np.float32(0.6957), np.float32(0.389), np.float32(0.8474), np.float32(0.6126), np.float32(0.752), np.float32(0.0), np.float32(0.0), np.float32(0.735), np.float32(0.6089), np.float32(0.9599), np.float32(0.9649)] 
+2026-10-19 15:28:59.091169: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 15:28:59.380137: lr: 0.000642 
+2026-10-19 15:28:59.380363: This epoch took 261.590020 s
+ 
+2026-10-19 15:28:59.380531: 
+epoch:  389 
+2026-10-19 15:33:16.638576: train loss : -0.8322 
+2026-10-19 15:33:21.984556: validation loss: -0.7012 
+2026-10-19 15:33:21.985486: Average global foreground Dice: [np.float32(0.9329), np.float32(0.7329), np.float32(0.8663), np.float32(0.8912), np.float32(0.8097), np.float32(0.9219), np.float32(0.8568), np.float32(0.5639), np.float32(0.0), np.float32(0.4627), np.float32(0.749), np.float32(0.7607), np.float32(0.578), np.float32(0.5555), np.float32(0.0), np.float32(0.0), np.float32(0.8099), np.float32(0.6298), np.float32(0.8228), np.float32(0.6438), np.float32(0.316), np.float32(0.7432), np.float32(0.922), np.float32(0.9134), np.float32(0.5917), np.float32(0.6294), np.float32(0.1989), np.float32(0.1977), np.float32(0.5432), np.float32(0.6991), np.float32(0.0), np.float32(0.0), np.float32(0.6528), np.float32(0.5787), np.float32(0.9588), np.float32(0.9683)] 
+2026-10-19 15:33:21.985696: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 15:33:22.271502: lr: 0.000641 
+2026-10-19 15:33:22.271858: This epoch took 262.891253 s
+ 
+2026-10-19 15:33:22.272088: 
+epoch:  390 
+2026-10-19 15:37:35.033892: train loss : -0.8305 
+2026-10-19 15:37:40.384908: validation loss: -0.7387 
+2026-10-19 15:37:40.386112: Average global foreground Dice: [np.float32(0.9359), np.float32(0.7366), np.float32(0.8822), np.float32(0.8803), np.float32(0.7941), np.float32(0.9335), np.float32(0.8802), np.float32(0.7578), np.float32(0.0), np.float32(0.516), np.float32(0.7385), np.float32(0.8169), np.float32(0.7267), np.float32(0.6602), np.float32(0.0), np.float32(0.0), np.float32(0.8176), np.float32(0.6533), np.float32(0.8384), np.float32(0.6895), np.float32(0.4032), np.float32(0.7798), np.float32(0.9301), np.float32(0.9137), np.float32(0.6272), np.float32(0.6952), np.float32(0.3019), np.float32(0.8399), np.float32(0.544), np.float32(0.7702), np.float32(0.0), np.float32(0.0), np.float32(0.7313), np.float32(0.6768), np.float32(0.951), np.float32(0.9673)] 
+2026-10-19 15:37:40.386438: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 15:37:40.682127: lr: 0.00064 
+2026-10-19 15:37:40.682362: This epoch took 258.410168 s
+ 
+2026-10-19 15:37:40.682696: 
+epoch:  391 
+2026-10-19 15:41:44.889536: train loss : -0.8387 
+2026-10-19 15:41:50.233079: validation loss: -0.7504 
+2026-10-19 15:41:50.234040: Average global foreground Dice: [np.float32(0.9436), np.float32(0.7771), np.float32(0.8677), np.float32(0.8874), np.float32(0.7943), np.float32(0.9253), np.float32(0.8947), np.float32(0.6126), np.float32(0.0), np.float32(0.5097), np.float32(0.7362), np.float32(0.8262), np.float32(0.7433), np.float32(0.6403), np.float32(0.0), np.float32(0.0), np.float32(0.8232), np.float32(0.6601), np.float32(0.8378), np.float32(0.7079), np.float32(0.449), np.float32(0.784), np.float32(0.9271), np.float32(0.9165), np.float32(0.6576), np.float32(0.6936), np.float32(0.3865), np.float32(0.7867), np.float32(0.6772), np.float32(0.7804), np.float32(0.0), np.float32(0.0), np.float32(0.7257), np.float32(0.6514), np.float32(0.9565), np.float32(0.9679)] 
+2026-10-19 15:41:50.234434: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 15:41:50.526578: lr: 0.000639 
+2026-10-19 15:41:50.526862: This epoch took 249.844034 s
+ 
+2026-10-19 15:41:50.526958: 
+epoch:  392 
+2026-10-19 15:46:09.206442: train loss : -0.8350 
+2026-10-19 15:46:14.560721: validation loss: -0.7146 
+2026-10-19 15:46:14.561946: Average global foreground Dice: [np.float32(0.9374), np.float32(0.7175), np.float32(0.8724), np.float32(0.8875), np.float32(0.7911), np.float32(0.9352), np.float32(0.8821), np.float32(0.728), np.float32(0.0), np.float32(0.5397), np.float32(0.7475), np.float32(0.8176), np.float32(0.6992), np.float32(0.585), np.float32(0.0), np.float32(0.0), np.float32(0.8235), np.float32(0.6508), np.float32(0.8338), np.float32(0.7109), np.float32(0.439), np.float32(0.7386), np.float32(0.9217), np.float32(0.9178), np.float32(0.6211), np.float32(0.6917), np.float32(0.3675), np.float32(0.8159), np.float32(0.5567), np.float32(0.7107), np.float32(0.0), np.float32(0.0), np.float32(0.7644), np.float32(0.6313), np.float32(0.9579), np.float32(0.9701)] 
+2026-10-19 15:46:14.562167: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 15:46:14.855016: lr: 0.000638 
+2026-10-19 15:46:14.855354: This epoch took 264.328313 s
+ 
+2026-10-19 15:46:14.855599: 
+epoch:  393 
+2026-10-19 15:50:23.927673: train loss : -0.8319 
+2026-10-19 15:50:29.285326: validation loss: -0.7309 
+2026-10-19 15:50:29.287391: Average global foreground Dice: [np.float32(0.939), np.float32(0.7468), np.float32(0.8708), np.float32(0.8909), np.float32(0.8181), np.float32(0.9291), np.float32(0.8901), np.float32(0.6247), np.float32(0.0), np.float32(0.5515), np.float32(0.7493), np.float32(0.8167), np.float32(0.7117), np.float32(0.6168), np.float32(0.0101), np.float32(0.0), np.float32(0.8188), np.float32(0.633), np.float32(0.8369), np.float32(0.7091), np.float32(0.3473), np.float32(0.7875), np.float32(0.9323), np.float32(0.9237), np.float32(0.6581), np.float32(0.6878), np.float32(0.3445), np.float32(0.834), np.float32(0.6306), np.float32(0.7797), np.float32(0.0), np.float32(0.0), np.float32(0.7134), np.float32(0.6442), np.float32(0.9612), np.float32(0.9689)] 
+2026-10-19 15:50:29.287693: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 15:50:29.578548: lr: 0.000637 
+2026-10-19 15:50:29.578804: This epoch took 254.723111 s
+ 
+2026-10-19 15:50:29.579096: 
+epoch:  394 
+2026-10-19 15:54:23.982306: train loss : -0.8362 
+2026-10-19 15:54:29.333542: validation loss: -0.7333 
+2026-10-19 15:54:29.334712: Average global foreground Dice: [np.float32(0.9411), np.float32(0.7752), np.float32(0.8734), np.float32(0.8988), np.float32(0.8243), np.float32(0.9283), np.float32(0.8932), np.float32(0.3682), np.float32(0.0), np.float32(0.5736), np.float32(0.7553), np.float32(0.7695), np.float32(0.7013), np.float32(0.5699), np.float32(0.0235), np.float32(0.0), np.float32(0.8322), np.float32(0.647), np.float32(0.8393), np.float32(0.7089), np.float32(0.3567), np.float32(0.7971), np.float32(0.9386), np.float32(0.933), np.float32(0.6674), np.float32(0.667), np.float32(0.3611), np.float32(0.7033), np.float32(0.6764), np.float32(0.7951), np.float32(0.0), np.float32(0.0), np.float32(0.747), np.float32(0.6785), np.float32(0.9617), np.float32(0.9699)] 
+2026-10-19 15:54:29.335099: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 15:54:29.615715: lr: 0.000636 
+2026-10-19 15:54:29.615999: This epoch took 240.036797 s
+ 
+2026-10-19 15:54:29.616085: 
+epoch:  395 
+2026-10-19 15:58:49.935828: train loss : -0.8309 
+2026-10-19 15:58:55.325520: validation loss: -0.7394 
+2026-10-19 15:58:55.326615: Average global foreground Dice: [np.float32(0.9417), np.float32(0.7768), np.float32(0.869), np.float32(0.8811), np.float32(0.8062), np.float32(0.9336), np.float32(0.8905), np.float32(0.6218), np.float32(0.0), np.float32(0.6131), np.float32(0.737), np.float32(0.8136), np.float32(0.7315), np.float32(0.5997), np.float32(0.0), np.float32(0.0), np.float32(0.8223), np.float32(0.6624), np.float32(0.8406), np.float32(0.7139), np.float32(0.3982), np.float32(0.792), np.float32(0.9337), np.float32(0.9179), np.float32(0.6426), np.float32(0.6888), np.float32(0.3651), np.float32(0.8427), np.float32(0.6795), np.float32(0.7464), np.float32(0.0), np.float32(0.0), np.float32(0.728), np.float32(0.6507), np.float32(0.9595), np.float32(0.9678)] 
+2026-10-19 15:58:55.326784: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 15:58:55.620800: lr: 0.000635 
+2026-10-19 15:58:55.621143: This epoch took 266.004999 s
+ 
+2026-10-19 15:58:55.621238: 
+epoch:  396 
+2026-10-19 16:03:32.059638: train loss : -0.8291 
+2026-10-19 16:03:37.405576: validation loss: -0.7405 
+2026-10-19 16:03:37.406623: Average global foreground Dice: [np.float32(0.9419), np.float32(0.7405), np.float32(0.8762), np.float32(0.8865), np.float32(0.8132), np.float32(0.9276), np.float32(0.8964), np.float32(0.4085), np.float32(0.0), np.float32(0.5092), np.float32(0.7416), np.float32(0.8002), np.float32(0.7273), np.float32(0.6099), np.float32(0.001), np.float32(0.0), np.float32(0.8314), np.float32(0.6651), np.float32(0.8447), np.float32(0.6787), np.float32(0.3637), np.float32(0.7762), np.float32(0.9411), np.float32(0.9295), np.float32(0.6753), np.float32(0.6535), np.float32(0.3535), np.float32(0.8309), np.float32(0.6589), np.float32(0.759), np.float32(0.0), np.float32(0.0), np.float32(0.7358), np.float32(0.6615), np.float32(0.9625), np.float32(0.9689)] 
+2026-10-19 16:03:37.406790: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 16:03:37.694965: lr: 0.000634 
+2026-10-19 16:03:37.695408: This epoch took 282.074117 s
+ 
+2026-10-19 16:03:37.695780: 
+epoch:  397 
+2026-10-19 16:07:36.710051: train loss : -0.8360 
+2026-10-19 16:07:42.112411: validation loss: -0.7416 
+2026-10-19 16:07:42.113608: Average global foreground Dice: [np.float32(0.9416), np.float32(0.7549), np.float32(0.8874), np.float32(0.8899), np.float32(0.8288), np.float32(0.9326), np.float32(0.8927), np.float32(0.4862), np.float32(0.0), np.float32(0.5354), np.float32(0.7446), np.float32(0.8219), np.float32(0.7334), np.float32(0.5995), np.float32(0.0), np.float32(0.0), np.float32(0.8362), np.float32(0.6555), np.float32(0.8441), np.float32(0.7069), np.float32(0.4077), np.float32(0.795), np.float32(0.9367), np.float32(0.9351), np.float32(0.677), np.float32(0.6938), np.float32(0.4016), np.float32(0.8212), np.float32(0.6256), np.float32(0.7673), np.float32(0.0), np.float32(0.0), np.float32(0.6757), np.float32(0.6278), np.float32(0.9609), np.float32(0.9702)] 
+2026-10-19 16:07:42.113980: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 16:07:42.413343: lr: 0.000633 
+2026-10-19 16:07:42.413752: This epoch took 244.717734 s
+ 
+2026-10-19 16:07:42.414057: 
+epoch:  398 
+2026-10-19 16:12:06.635435: train loss : -0.8390 
+2026-10-19 16:12:11.967870: validation loss: -0.7318 
+2026-10-19 16:12:11.969083: Average global foreground Dice: [np.float32(0.9366), np.float32(0.7286), np.float32(0.873), np.float32(0.8689), np.float32(0.7503), np.float32(0.9419), np.float32(0.8956), np.float32(0.5908), np.float32(0.0), np.float32(0.5368), np.float32(0.743), np.float32(0.8102), np.float32(0.7423), np.float32(0.6612), np.float32(0.0), np.float32(0.0), np.float32(0.8279), np.float32(0.5868), np.float32(0.8438), np.float32(0.7217), np.float32(0.3208), np.float32(0.7531), np.float32(0.9291), np.float32(0.9165), np.float32(0.6786), np.float32(0.6882), np.float32(0.3817), np.float32(0.7722), np.float32(0.6012), np.float32(0.7348), np.float32(0.0), np.float32(0.0), np.float32(0.7107), np.float32(0.662), np.float32(0.959), np.float32(0.9695)] 
+2026-10-19 16:12:11.969334: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 16:12:12.254812: lr: 0.000632 
+2026-10-19 16:12:12.255249: This epoch took 269.840964 s
+ 
+2026-10-19 16:12:12.255497: 
+epoch:  399 
+2026-10-19 16:16:22.932757: train loss : -0.8300 
+2026-10-19 16:16:28.279668: validation loss: -0.7391 
+2026-10-19 16:16:28.280597: Average global foreground Dice: [np.float32(0.9383), np.float32(0.73), np.float32(0.8839), np.float32(0.8916), np.float32(0.8109), np.float32(0.9348), np.float32(0.8976), np.float32(0.5471), np.float32(0.0), np.float32(0.5896), np.float32(0.7597), np.float32(0.8531), np.float32(0.7307), np.float32(0.6149), np.float32(0.0), np.float32(0.0), np.float32(0.8335), np.float32(0.6647), np.float32(0.8474), np.float32(0.6927), np.float32(0.2935), np.float32(0.7975), np.float32(0.9341), np.float32(0.9238), np.float32(0.6671), np.float32(0.6938), np.float32(0.3779), np.float32(0.8727), np.float32(0.6303), np.float32(0.734), np.float32(0.0), np.float32(0.0), np.float32(0.737), np.float32(0.6565), np.float32(0.9589), np.float32(0.9679)] 
+2026-10-19 16:16:28.280777: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 16:16:28.567928: lr: 0.000631 
+2026-10-19 16:16:28.568342: saving scheduled checkpoint file... 
+2026-10-19 16:16:28.577172: saving checkpoint... 
+2026-10-19 16:16:28.711463: done, saving took 0.14 seconds 
+2026-10-19 16:16:28.712893: done 
+2026-10-19 16:16:28.713052: This epoch took 256.457321 s
+ 
+2026-10-19 16:16:28.713123: 
+epoch:  400 
+2026-10-19 16:20:37.271622: train loss : -0.8366 
+2026-10-19 16:20:42.624027: validation loss: -0.7492 
+2026-10-19 16:20:42.625065: Average global foreground Dice: [np.float32(0.9385), np.float32(0.7538), np.float32(0.8827), np.float32(0.8972), np.float32(0.8238), np.float32(0.9318), np.float32(0.8986), np.float32(0.5616), np.float32(0.0), np.float32(0.5554), np.float32(0.7482), np.float32(0.8361), np.float32(0.7363), np.float32(0.6351), np.float32(0.0), np.float32(0.0), np.float32(0.829), np.float32(0.6703), np.float32(0.843), np.float32(0.6953), np.float32(0.2814), np.float32(0.7881), np.float32(0.9424), np.float32(0.9283), np.float32(0.6778), np.float32(0.6796), np.float32(0.4236), np.float32(0.8475), np.float32(0.6706), np.float32(0.7839), np.float32(0.0), np.float32(0.0), np.float32(0.7474), np.float32(0.6587), np.float32(0.9639), np.float32(0.9697)] 
+2026-10-19 16:20:42.625474: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 16:20:42.936394: lr: 0.00063 
+2026-10-19 16:20:42.936620: This epoch took 254.223435 s
+ 
+2026-10-19 16:20:42.936744: 
+epoch:  401 
+2026-10-19 16:24:26.454123: train loss : -0.8362 
+2026-10-19 16:24:31.790066: validation loss: -0.7332 
+2026-10-19 16:24:31.790952: Average global foreground Dice: [np.float32(0.939), np.float32(0.7311), np.float32(0.8884), np.float32(0.8721), np.float32(0.782), np.float32(0.933), np.float32(0.8873), np.float32(0.7016), np.float32(0.0), np.float32(0.6129), np.float32(0.7472), np.float32(0.8424), np.float32(0.7295), np.float32(0.5728), np.float32(0.0), np.float32(0.0), np.float32(0.8328), np.float32(0.6626), np.float32(0.8497), np.float32(0.7156), np.float32(0.2823), np.float32(0.7891), np.float32(0.9262), np.float32(0.9271), np.float32(0.6551), np.float32(0.7116), np.float32(0.3682), np.float32(0.8287), np.float32(0.6153), np.float32(0.7672), np.float32(0.0), np.float32(0.0), np.float32(0.7298), np.float32(0.6534), np.float32(0.9568), np.float32(0.9676)] 
+2026-10-19 16:24:31.791109: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 16:24:32.079169: lr: 0.00063 
+2026-10-19 16:24:32.079527: This epoch took 229.142559 s
+ 
+2026-10-19 16:24:32.079777: 
+epoch:  402 
+2026-10-19 16:28:31.507590: train loss : -0.8283 
+2026-10-19 16:28:36.853255: validation loss: -0.7501 
+2026-10-19 16:28:36.854215: Average global foreground Dice: [np.float32(0.9432), np.float32(0.7473), np.float32(0.882), np.float32(0.8928), np.float32(0.8186), np.float32(0.928), np.float32(0.8462), np.float32(0.6555), np.float32(0.0), np.float32(0.6142), np.float32(0.7345), np.float32(0.8083), np.float32(0.714), np.float32(0.6036), np.float32(0.0), np.float32(0.0), np.float32(0.8359), np.float32(0.6925), np.float32(0.8484), np.float32(0.7258), np.float32(0.2812), np.float32(0.7722), np.float32(0.9376), np.float32(0.9221), np.float32(0.6699), np.float32(0.7244), np.float32(0.3995), np.float32(0.8626), np.float32(0.6379), np.float32(0.7961), np.float32(0.0), np.float32(0.0), np.float32(0.732), np.float32(0.6508), np.float32(0.9621), np.float32(0.9669)] 
+2026-10-19 16:28:36.854381: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 16:28:37.145066: lr: 0.000629 
+2026-10-19 16:28:37.145341: This epoch took 245.065399 s
+ 
+2026-10-19 16:28:37.145424: 
+epoch:  403 
+2026-10-19 16:32:40.939025: train loss : -0.8383 
+2026-10-19 16:32:46.297896: validation loss: -0.7428 
+2026-10-19 16:32:46.299056: Average global foreground Dice: [np.float32(0.9381), np.float32(0.7604), np.float32(0.8726), np.float32(0.884), np.float32(0.8127), np.float32(0.9278), np.float32(0.8893), np.float32(0.6856), np.float32(0.0), np.float32(0.5818), np.float32(0.747), np.float32(0.8307), np.float32(0.7223), np.float32(0.6422), np.float32(0.0), np.float32(0.0), np.float32(0.8353), np.float32(0.6716), np.float32(0.8432), np.float32(0.7066), np.float32(0.3075), np.float32(0.7948), np.float32(0.9314), np.float32(0.9207), np.float32(0.663), np.float32(0.707), np.float32(0.3291), np.float32(0.8541), np.float32(0.5874), np.float32(0.7823), np.float32(0.0), np.float32(0.0), np.float32(0.7535), np.float32(0.6927), np.float32(0.9552), np.float32(0.9664)] 
+2026-10-19 16:32:46.299287: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 16:32:46.602045: lr: 0.000628 
+2026-10-19 16:32:46.602410: This epoch took 249.456841 s
+ 
+2026-10-19 16:32:46.602561: 
+epoch:  404 
+2026-10-19 16:36:34.331391: train loss : -0.8305 
+2026-10-19 16:36:39.666638: validation loss: -0.7544 
+2026-10-19 16:36:39.668020: Average global foreground Dice: [np.float32(0.9472), np.float32(0.7712), np.float32(0.8505), np.float32(0.8684), np.float32(0.8326), np.float32(0.9269), np.float32(0.899), np.float32(0.6421), np.float32(0.0), np.float32(0.5378), np.float32(0.7461), np.float32(0.8252), np.float32(0.7736), np.float32(0.6226), np.float32(0.0), np.float32(0.0), np.float32(0.839), np.float32(0.6611), np.float32(0.8416), np.float32(0.7078), np.float32(0.3364), np.float32(0.8056), np.float32(0.935), np.float32(0.9297), np.float32(0.6847), np.float32(0.6651), np.float32(0.4077), np.float32(0.8163), np.float32(0.6991), np.float32(0.8028), np.float32(0.0), np.float32(0.0), np.float32(0.7012), np.float32(0.6492), np.float32(0.9592), np.float32(0.9694)] 
+2026-10-19 16:36:39.668314: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 16:36:39.945679: lr: 0.000627 
+2026-10-19 16:36:39.945962: This epoch took 233.343244 s
+ 
+2026-10-19 16:36:39.946069: 
+epoch:  405 
+2026-10-19 16:40:46.837315: train loss : -0.8450 
+2026-10-19 16:40:52.172090: validation loss: -0.7288 
+2026-10-19 16:40:52.173146: Average global foreground Dice: [np.float32(0.9358), np.float32(0.7683), np.float32(0.8641), np.float32(0.8906), np.float32(0.8166), np.float32(0.9337), np.float32(0.8925), np.float32(0.7456), np.float32(0.0), np.float32(0.5297), np.float32(0.736), np.float32(0.8249), np.float32(0.7394), np.float32(0.5852), np.float32(0.0), np.float32(0.0), np.float32(0.8322), np.float32(0.6672), np.float32(0.8496), np.float32(0.7233), np.float32(0.3433), np.float32(0.7641), np.float32(0.9147), np.float32(0.9111), np.float32(0.6766), np.float32(0.6617), np.float32(0.367), np.float32(0.794), np.float32(0.6294), np.float32(0.7492), np.float32(0.0), np.float32(0.0), np.float32(0.6874), np.float32(0.6346), np.float32(0.9607), np.float32(0.9702)] 
+2026-10-19 16:40:52.173486: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 16:40:52.464306: lr: 0.000626 
+2026-10-19 16:40:52.464731: This epoch took 252.518575 s
+ 
+2026-10-19 16:40:52.465013: 
+epoch:  406 
+2026-10-19 16:45:17.207758: train loss : -0.8352 
+2026-10-19 16:45:22.555278: validation loss: -0.7421 
+2026-10-19 16:45:22.556171: Average global foreground Dice: [np.float32(0.9415), np.float32(0.7416), np.float32(0.8574), np.float32(0.8919), np.float32(0.796), np.float32(0.9302), np.float32(0.8785), np.float32(0.6412), np.float32(0.0), np.float32(0.5263), np.float32(0.7441), np.float32(0.8212), np.float32(0.7265), np.float32(0.5982), np.float32(0.0), np.float32(0.0), np.float32(0.8303), np.float32(0.671), np.float32(0.8401), np.float32(0.7162), np.float32(0.3746), np.float32(0.7853), np.float32(0.9281), np.float32(0.927), np.float32(0.6779), np.float32(0.6946), np.float32(0.3942), np.float32(0.8036), np.float32(0.6336), np.float32(0.8012), np.float32(0.0), np.float32(0.0), np.float32(0.7057), np.float32(0.6519), np.float32(0.9578), np.float32(0.9701)] 
+2026-10-19 16:45:22.556325: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 16:45:22.853463: lr: 0.000625 
+2026-10-19 16:45:22.853862: This epoch took 270.388638 s
+ 
+2026-10-19 16:45:22.853966: 
+epoch:  407 
+2026-10-19 16:49:00.828494: train loss : -0.8301 
+2026-10-19 16:49:06.167303: validation loss: -0.7426 
+2026-10-19 16:49:06.168357: Average global foreground Dice: [np.float32(0.9313), np.float32(0.7279), np.float32(0.8708), np.float32(0.8687), np.float32(0.8058), np.float32(0.9336), np.float32(0.8985), np.float32(0.7181), np.float32(0.0), np.float32(0.4695), np.float32(0.7813), np.float32(0.839), np.float32(0.6455), np.float32(0.6025), np.float32(0.0), np.float32(0.0), np.float32(0.8345), np.float32(0.6854), np.float32(0.8406), np.float32(0.7294), np.float32(0.3596), np.float32(0.7648), np.float32(0.9329), np.float32(0.9221), np.float32(0.6837), np.float32(0.7123), np.float32(0.3956), np.float32(0.8335), np.float32(0.5998), np.float32(0.7878), np.float32(0.0), np.float32(0.0), np.float32(0.7347), np.float32(0.6418), np.float32(0.9549), np.float32(0.9685)] 
+2026-10-19 16:49:06.168819: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 16:49:06.451998: lr: 0.000624 
+2026-10-19 16:49:06.452339: This epoch took 223.598314 s
+ 
+2026-10-19 16:49:06.452536: 
+epoch:  408 
+2026-10-19 16:52:56.477472: train loss : -0.8324 
+2026-10-19 16:53:01.822071: validation loss: -0.7540 
+2026-10-19 16:53:01.823071: Average global foreground Dice: [np.float32(0.9445), np.float32(0.7506), np.float32(0.87), np.float32(0.8793), np.float32(0.7982), np.float32(0.9312), np.float32(0.8983), np.float32(0.7884), np.float32(0.0), np.float32(0.5468), np.float32(0.7598), np.float32(0.8344), np.float32(0.7332), np.float32(0.6669), np.float32(0.0), np.float32(0.0), np.float32(0.817), np.float32(0.653), np.float32(0.8274), np.float32(0.6884), np.float32(0.2841), np.float32(0.7641), np.float32(0.9333), np.float32(0.9169), np.float32(0.6423), np.float32(0.6937), np.float32(0.4013), np.float32(0.8255), np.float32(0.6438), np.float32(0.7879), np.float32(0.0), np.float32(0.0), np.float32(0.7141), np.float32(0.67), np.float32(0.9518), np.float32(0.9679)] 
+2026-10-19 16:53:01.823224: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 16:53:02.140893: lr: 0.000623 
+2026-10-19 16:53:02.141106: This epoch took 235.688419 s
+ 
+2026-10-19 16:53:02.141183: 
+epoch:  409 
+2026-10-19 16:56:39.014712: train loss : -0.8359 
+2026-10-19 16:56:44.353803: validation loss: -0.7390 
+2026-10-19 16:56:44.354758: Average global foreground Dice: [np.float32(0.9457), np.float32(0.746), np.float32(0.8836), np.float32(0.8943), np.float32(0.8047), np.float32(0.9356), np.float32(0.8952), np.float32(0.7868), np.float32(0.0), np.float32(0.428), np.float32(0.7564), np.float32(0.8339), np.float32(0.6883), np.float32(0.6048), np.float32(0.0), np.float32(0.0), np.float32(0.8377), np.float32(0.6622), np.float32(0.8474), np.float32(0.7332), np.float32(0.3772), np.float32(0.7864), np.float32(0.9399), np.float32(0.9345), np.float32(0.6834), np.float32(0.7069), np.float32(0.3961), np.float32(0.8567), np.float32(0.6202), np.float32(0.7915), np.float32(0.0), np.float32(0.0), np.float32(0.7247), np.float32(0.675), np.float32(0.96), np.float32(0.9713)] 
+2026-10-19 16:56:44.354997: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 16:56:44.647182: lr: 0.000622 
+2026-10-19 16:56:44.647647: This epoch took 222.506388 s
+ 
+2026-10-19 16:56:44.647886: 
+epoch:  410 
+2026-10-19 17:00:16.671106: train loss : -0.8382 
+2026-10-19 17:00:22.000028: validation loss: -0.7353 
+2026-10-19 17:00:22.001144: Average global foreground Dice: [np.float32(0.9441), np.float32(0.7448), np.float32(0.8759), np.float32(0.8949), np.float32(0.8069), np.float32(0.9376), np.float32(0.8813), np.float32(0.6924), np.float32(0.0), np.float32(0.5345), np.float32(0.7571), np.float32(0.8369), np.float32(0.6901), np.float32(0.6609), np.float32(0.0), np.float32(0.0), np.float32(0.8287), np.float32(0.6669), np.float32(0.8327), np.float32(0.6981), np.float32(0.3457), np.float32(0.7999), np.float32(0.936), np.float32(0.934), np.float32(0.6331), np.float32(0.6985), np.float32(0.4095), np.float32(0.8548), np.float32(0.6269), np.float32(0.7814), np.float32(0.0), np.float32(0.0), np.float32(0.7301), np.float32(0.6325), np.float32(0.9529), np.float32(0.9691)] 
+2026-10-19 17:00:22.001504: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 17:00:22.288178: lr: 0.000621 
+2026-10-19 17:00:22.288637: This epoch took 217.640553 s
+ 
+2026-10-19 17:00:22.288940: 
+epoch:  411 
+2026-10-19 17:04:07.794784: train loss : -0.8300 
+2026-10-19 17:04:13.146435: validation loss: -0.7316 
+2026-10-19 17:04:13.147415: Average global foreground Dice: [np.float32(0.9457), np.float32(0.72), np.float32(0.8758), np.float32(0.8824), np.float32(0.7856), np.float32(0.9389), np.float32(0.8848), np.float32(0.7844), np.float32(0.0), np.float32(0.5547), np.float32(0.7341), np.float32(0.8313), np.float32(0.7254), np.float32(0.6476), np.float32(0.0), np.float32(0.0), np.float32(0.8187), np.float32(0.6447), np.float32(0.8293), np.float32(0.6665), np.float32(0.2484), np.float32(0.7672), np.float32(0.9348), np.float32(0.9311), np.float32(0.6536), np.float32(0.6951), np.float32(0.3853), np.float32(0.8671), np.float32(0.5898), np.float32(0.7882), np.float32(0.0), np.float32(0.0), np.float32(0.6969), np.float32(0.6675), np.float32(0.9554), np.float32(0.9651)] 
+2026-10-19 17:04:13.147696: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 17:04:13.423763: lr: 0.00062 
+2026-10-19 17:04:13.424188: This epoch took 231.135010 s
+ 
+2026-10-19 17:04:13.424536: 
+epoch:  412 
+2026-10-19 17:08:08.005357: train loss : -0.8339 
+2026-10-19 17:08:13.345959: validation loss: -0.7416 
+2026-10-19 17:08:13.346824: Average global foreground Dice: [np.float32(0.943), np.float32(0.7555), np.float32(0.8486), np.float32(0.8727), np.float32(0.7966), np.float32(0.9352), np.float32(0.8791), np.float32(0.5285), np.float32(0.0), np.float32(0.5444), np.float32(0.7495), np.float32(0.8229), np.float32(0.7566), np.float32(0.6676), np.float32(0.0), np.float32(0.0), np.float32(0.8219), np.float32(0.6443), np.float32(0.8343), np.float32(0.7), np.float32(0.3298), np.float32(0.7835), np.float32(0.9282), np.float32(0.9192), np.float32(0.6445), np.float32(0.6858), np.float32(0.4429), np.float32(0.8366), np.float32(0.6571), np.float32(0.7631), np.float32(0.0), np.float32(0.0), np.float32(0.7019), np.float32(0.6316), np.float32(0.9518), np.float32(0.9674)] 
+2026-10-19 17:08:13.347090: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 17:08:13.646368: lr: 0.000619 
+2026-10-19 17:08:13.646610: This epoch took 240.221604 s
+ 
+2026-10-19 17:08:13.646787: 
+epoch:  413 
+2026-10-19 17:11:49.359350: train loss : -0.8398 
+2026-10-19 17:11:54.684996: validation loss: -0.7288 
+2026-10-19 17:11:54.686228: Average global foreground Dice: [np.float32(0.9408), np.float32(0.7191), np.float32(0.8628), np.float32(0.8751), np.float32(0.7675), np.float32(0.9355), np.float32(0.8723), np.float32(0.6036), np.float32(0.0), np.float32(0.5649), np.float32(0.738), np.float32(0.8047), np.float32(0.6973), np.float32(0.6068), np.float32(0.0), np.float32(0.0), np.float32(0.8329), np.float32(0.6495), np.float32(0.8429), np.float32(0.7171), np.float32(0.3397), np.float32(0.7891), np.float32(0.9316), np.float32(0.92), np.float32(0.6427), np.float32(0.7025), np.float32(0.4127), np.float32(0.7133), np.float32(0.6365), np.float32(0.7668), np.float32(0.0), np.float32(0.0), np.float32(0.7119), np.float32(0.6281), np.float32(0.9538), np.float32(0.9684)] 
+2026-10-19 17:11:54.686569: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 17:11:54.976699: lr: 0.000618 
+2026-10-19 17:11:54.976935: This epoch took 221.330074 s
+ 
+2026-10-19 17:11:54.977121: 
+epoch:  414 
+2026-10-19 17:15:45.903707: train loss : -0.8336 
+2026-10-19 17:15:51.257186: validation loss: -0.7356 
+2026-10-19 17:15:51.258075: Average global foreground Dice: [np.float32(0.9415), np.float32(0.7555), np.float32(0.8658), np.float32(0.8936), np.float32(0.7986), np.float32(0.9263), np.float32(0.8917), np.float32(0.727), np.float32(0.0), np.float32(0.4322), np.float32(0.7455), np.float32(0.8208), np.float32(0.7225), np.float32(0.6228), np.float32(0.0), np.float32(0.0), np.float32(0.8275), np.float32(0.6687), np.float32(0.8403), np.float32(0.7128), np.float32(0.3074), np.float32(0.8008), np.float32(0.9338), np.float32(0.9331), np.float32(0.6403), np.float32(0.6734), np.float32(0.3263), np.float32(0.8281), np.float32(0.6569), np.float32(0.7705), np.float32(0.0), np.float32(0.0), np.float32(0.7261), np.float32(0.6899), np.float32(0.9596), np.float32(0.9683)] 
+2026-10-19 17:15:51.258886: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 17:15:51.548549: lr: 0.000617 
+2026-10-19 17:15:51.548840: This epoch took 236.571503 s
+ 
+2026-10-19 17:15:51.548940: 
+epoch:  415 
+2026-10-19 17:19:29.702423: train loss : -0.8347 
+2026-10-19 17:19:35.039805: validation loss: -0.7410 
+2026-10-19 17:19:35.040998: Average global foreground Dice: [np.float32(0.9377), np.float32(0.7596), np.float32(0.8727), np.float32(0.8916), np.float32(0.8258), np.float32(0.9265), np.float32(0.8762), np.float32(0.6905), np.float32(0.0), np.float32(0.6178), np.float32(0.7666), np.float32(0.8295), np.float32(0.7386), np.float32(0.6259), np.float32(0.0), np.float32(0.0), np.float32(0.8182), np.float32(0.6426), np.float32(0.8292), np.float32(0.692), np.float32(0.2596), np.float32(0.78), np.float32(0.9316), np.float32(0.9272), np.float32(0.6316), np.float32(0.6725), np.float32(0.363), np.float32(0.7443), np.float32(0.6842), np.float32(0.7829), np.float32(0.0), np.float32(0.0), np.float32(0.6887), np.float32(0.6871), np.float32(0.9534), np.float32(0.9666)] 
+2026-10-19 17:19:35.041385: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 17:19:35.330175: lr: 0.000616 
+2026-10-19 17:19:35.330584: This epoch took 223.781576 s
+ 
+2026-10-19 17:19:35.330885: 
+epoch:  416 
+2026-10-19 17:24:01.916646: train loss : -0.8392 
+2026-10-19 17:24:07.257797: validation loss: -0.7451 
+2026-10-19 17:24:07.258763: Average global foreground Dice: [np.float32(0.9443), np.float32(0.7301), np.float32(0.8827), np.float32(0.8872), np.float32(0.7982), np.float32(0.9325), np.float32(0.8958), np.float32(0.8108), np.float32(0.0), np.float32(0.6227), np.float32(0.7575), np.float32(0.8387), np.float32(0.6999), np.float32(0.5777), np.float32(0.0), np.float32(0.0), np.float32(0.8248), np.float32(0.6674), np.float32(0.8466), np.float32(0.7145), np.float32(0.3315), np.float32(0.7989), np.float32(0.9307), np.float32(0.9291), np.float32(0.6579), np.float32(0.7051), np.float32(0.4215), np.float32(0.8641), np.float32(0.6502), np.float32(0.8085), np.float32(0.0), np.float32(0.0), np.float32(0.7424), np.float32(0.6882), np.float32(0.9564), np.float32(0.9702)] 
+2026-10-19 17:24:07.258954: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 17:24:07.543049: lr: 0.000615 
+2026-10-19 17:24:07.543618: This epoch took 272.212511 s
+ 
+2026-10-19 17:24:07.543818: 
+epoch:  417 
+2026-10-19 17:28:09.610404: train loss : -0.8333 
+2026-10-19 17:28:14.948905: validation loss: -0.7194 
+2026-10-19 17:28:14.949909: Average global foreground Dice: [np.float32(0.9465), np.float32(0.7112), np.float32(0.8639), np.float32(0.8783), np.float32(0.7805), np.float32(0.9283), np.float32(0.8902), np.float32(0.6982), np.float32(0.0), np.float32(0.5905), np.float32(0.7534), np.float32(0.8205), np.float32(0.728), np.float32(0.6167), np.float32(0.002), np.float32(0.0), np.float32(0.8251), np.float32(0.6585), np.float32(0.842), np.float32(0.701), np.float32(0.3281), np.float32(0.7739), np.float32(0.9294), np.float32(0.9248), np.float32(0.6329), np.float32(0.7003), np.float32(0.38), np.float32(0.8647), np.float32(0.5621), np.float32(0.7363), np.float32(0.0), np.float32(0.0), np.float32(0.7335), np.float32(0.6692), np.float32(0.9565), np.float32(0.9683)] 
+2026-10-19 17:28:14.950103: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 17:28:15.232434: lr: 0.000614 
+2026-10-19 17:28:15.232822: This epoch took 247.688911 s
+ 
+2026-10-19 17:28:15.233100: 
+epoch:  418 
+2026-10-19 17:31:48.618049: train loss : -0.8407 
+2026-10-19 17:31:53.944234: validation loss: -0.7340 
+2026-10-19 17:31:53.945237: Average global foreground Dice: [np.float32(0.9503), np.float32(0.7414), np.float32(0.873), np.float32(0.8902), np.float32(0.8281), np.float32(0.9301), np.float32(0.8813), np.float32(0.7387), np.float32(0.0), np.float32(0.474), np.float32(0.7491), np.float32(0.8245), np.float32(0.7047), np.float32(0.6178), np.float32(0.0), np.float32(0.0), np.float32(0.8393), np.float32(0.6838), np.float32(0.8435), np.float32(0.734), np.float32(0.3608), np.float32(0.7832), np.float32(0.9383), np.float32(0.9403), np.float32(0.632), np.float32(0.7058), np.float32(0.3843), np.float32(0.8432), np.float32(0.6052), np.float32(0.7558), np.float32(0.0), np.float32(0.0), np.float32(0.7337), np.float32(0.6991), np.float32(0.9609), np.float32(0.9673)] 
+2026-10-19 17:31:53.945660: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 17:31:54.240244: lr: 0.000613 
+2026-10-19 17:31:54.240581: This epoch took 219.007321 s
+ 
+2026-10-19 17:31:54.240767: 
+epoch:  419 
+2026-10-19 17:36:00.633164: train loss : -0.8314 
+2026-10-19 17:36:05.956937: validation loss: -0.7387 
+2026-10-19 17:36:05.957955: Average global foreground Dice: [np.float32(0.9449), np.float32(0.7514), np.float32(0.858), np.float32(0.8798), np.float32(0.8108), np.float32(0.9348), np.float32(0.884), np.float32(0.6559), np.float32(0.0), np.float32(0.5513), np.float32(0.7653), np.float32(0.8453), np.float32(0.7509), np.float32(0.6833), np.float32(0.0), np.float32(0.0), np.float32(0.8272), np.float32(0.6566), np.float32(0.8309), np.float32(0.7062), np.float32(0.3065), np.float32(0.7867), np.float32(0.9321), np.float32(0.9119), np.float32(0.6503), np.float32(0.6719), np.float32(0.3881), np.float32(0.7704), np.float32(0.6428), np.float32(0.7944), np.float32(0.0), np.float32(0.0), np.float32(0.7124), np.float32(0.657), np.float32(0.9586), np.float32(0.968)] 
+2026-10-19 17:36:05.958284: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 17:36:06.261163: lr: 0.000612 
+2026-10-19 17:36:06.261446: This epoch took 252.020543 s
+ 
+2026-10-19 17:36:06.261655: 
+epoch:  420 
+2026-10-19 17:39:43.832290: train loss : -0.8319 
+2026-10-19 17:39:49.164944: validation loss: -0.7356 
+2026-10-19 17:39:49.165982: Average global foreground Dice: [np.float32(0.9461), np.float32(0.7253), np.float32(0.8717), np.float32(0.8884), np.float32(0.8094), np.float32(0.932), np.float32(0.8931), np.float32(0.735), np.float32(0.0), np.float32(0.6062), np.float32(0.7543), np.float32(0.8492), np.float32(0.6997), np.float32(0.6117), np.float32(0.0), np.float32(0.0), np.float32(0.8296), np.float32(0.6739), np.float32(0.8449), np.float32(0.721), np.float32(0.3711), np.float32(0.7869), np.float32(0.9352), np.float32(0.9242), np.float32(0.6476), np.float32(0.7077), np.float32(0.3943), np.float32(0.7809), np.float32(0.6273), np.float32(0.7898), np.float32(0.0), np.float32(0.0), np.float32(0.7239), np.float32(0.6688), np.float32(0.9568), np.float32(0.9691)] 
+2026-10-19 17:39:49.166324: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 17:39:49.449748: lr: 0.000612 
+2026-10-19 17:39:49.450025: This epoch took 223.188245 s
+ 
+2026-10-19 17:39:49.450115: 
+epoch:  421 
+2026-10-19 17:43:59.010264: train loss : -0.8396 
+2026-10-19 17:44:04.356104: validation loss: -0.7316 
+2026-10-19 17:44:04.358194: Average global foreground Dice: [np.float32(0.9443), np.float32(0.7065), np.float32(0.873), np.float32(0.8736), np.float32(0.7973), np.float32(0.9263), np.float32(0.886), np.float32(0.644), np.float32(0.0), np.float32(0.6022), np.float32(0.763), np.float32(0.8547), np.float32(0.699), np.float32(0.6351), np.float32(0.0), np.float32(0.0), np.float32(0.8266), np.float32(0.673), np.float32(0.8432), np.float32(0.7127), np.float32(0.2654), np.float32(0.7922), np.float32(0.9335), np.float32(0.9265), np.float32(0.6138), np.float32(0.7057), np.float32(0.373), np.float32(0.856), np.float32(0.6054), np.float32(0.7947), np.float32(0.0), np.float32(0.0), np.float32(0.7273), np.float32(0.6811), np.float32(0.957), np.float32(0.9683)] 
+2026-10-19 17:44:04.358660: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 17:44:04.669733: lr: 0.000611 
+2026-10-19 17:44:04.670020: This epoch took 255.219836 s
+ 
+2026-10-19 17:44:04.670134: 
+epoch:  422 
+2026-10-19 17:47:47.892909: train loss : -0.8362 
+2026-10-19 17:47:53.230593: validation loss: -0.7320 
+2026-10-19 17:47:53.231636: Average global foreground Dice: [np.float32(0.9482), np.float32(0.7249), np.float32(0.8795), np.float32(0.8774), np.float32(0.7698), np.float32(0.9299), np.float32(0.888), np.float32(0.4238), np.float32(0.0), np.float32(0.5793), np.float32(0.7425), np.float32(0.8377), np.float32(0.7453), np.float32(0.6174), np.float32(0.0), np.float32(0.0), np.float32(0.8246), np.float32(0.6642), np.float32(0.8372), np.float32(0.7142), np.float32(0.2837), np.float32(0.781), np.float32(0.939), np.float32(0.9275), np.float32(0.6431), np.float32(0.7116), np.float32(0.3125), np.float32(0.8565), np.float32(0.6173), np.float32(0.7713), np.float32(0.0), np.float32(0.0), np.float32(0.7389), np.float32(0.6865), np.float32(0.9486), np.float32(0.969)] 
+2026-10-19 17:47:53.231840: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 17:47:53.505331: lr: 0.00061 
+2026-10-19 17:47:53.505563: This epoch took 228.835365 s
+ 
+2026-10-19 17:47:53.505639: 
+epoch:  423 
+2026-10-19 17:51:53.463926: train loss : -0.8351 
+2026-10-19 17:51:58.801974: validation loss: -0.7293 
+2026-10-19 17:51:58.802831: Average global foreground Dice: [np.float32(0.9468), np.float32(0.7292), np.float32(0.8684), np.float32(0.8762), np.float32(0.7937), np.float32(0.9341), np.float32(0.8872), np.float32(0.4767), np.float32(0.0), np.float32(0.5463), np.float32(0.7677), np.float32(0.838), np.float32(0.7506), np.float32(0.6282), np.float32(0.0), np.float32(0.0), np.float32(0.8303), np.float32(0.6651), np.float32(0.8341), np.float32(0.6994), np.float32(0.2666), np.float32(0.7772), np.float32(0.9328), np.float32(0.9247), np.float32(0.5837), np.float32(0.6686), np.float32(0.3681), np.float32(0.8759), np.float32(0.6241), np.float32(0.7497), np.float32(0.0), np.float32(0.0), np.float32(0.682), np.float32(0.6578), np.float32(0.9559), np.float32(0.9689)] 
+2026-10-19 17:51:58.802980: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 17:51:59.077965: lr: 0.000609 
+2026-10-19 17:51:59.078252: This epoch took 245.572557 s
+ 
+2026-10-19 17:51:59.078349: 
+epoch:  424 
+2026-10-19 17:55:46.215168: train loss : -0.8399 
+2026-10-19 17:55:51.554566: validation loss: -0.7328 
+2026-10-19 17:55:51.555486: Average global foreground Dice: [np.float32(0.9478), np.float32(0.7397), np.float32(0.8753), np.float32(0.8864), np.float32(0.825), np.float32(0.9338), np.float32(0.8964), np.float32(0.6267), np.float32(0.0), np.float32(0.434), np.float32(0.7574), np.float32(0.8269), np.float32(0.7501), np.float32(0.6226), np.float32(0.0), np.float32(0.0), np.float32(0.8354), np.float32(0.6749), np.float32(0.8484), np.float32(0.7204), np.float32(0.347), np.float32(0.7963), np.float32(0.9377), np.float32(0.9241), np.float32(0.6453), np.float32(0.701), np.float32(0.3897), np.float32(0.8716), np.float32(0.6252), np.float32(0.7621), np.float32(0.0), np.float32(0.0), np.float32(0.7516), np.float32(0.6907), np.float32(0.959), np.float32(0.9701)] 
+2026-10-19 17:55:51.555642: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 17:55:51.836731: lr: 0.000608 
+2026-10-19 17:55:51.837173: This epoch took 232.758735 s
+ 
+2026-10-19 17:55:51.837369: 
+epoch:  425 
+2026-10-19 17:59:42.133137: train loss : -0.8379 
+2026-10-19 17:59:47.467875: validation loss: -0.7388 
+2026-10-19 17:59:47.468831: Average global foreground Dice: [np.float32(0.9404), np.float32(0.7329), np.float32(0.8672), np.float32(0.8961), np.float32(0.826), np.float32(0.936), np.float32(0.8919), np.float32(0.5512), np.float32(0.0), np.float32(0.5561), np.float32(0.7483), np.float32(0.8379), np.float32(0.749), np.float32(0.5884), np.float32(0.0), np.float32(0.0), np.float32(0.8339), np.float32(0.6721), np.float32(0.8404), np.float32(0.7073), np.float32(0.3051), np.float32(0.7481), np.float32(0.9386), np.float32(0.9289), np.float32(0.599), np.float32(0.6959), np.float32(0.3172), np.float32(0.8228), np.float32(0.6563), np.float32(0.7883), np.float32(0.0), np.float32(0.0), np.float32(0.7566), np.float32(0.6649), np.float32(0.9635), np.float32(0.9709)] 
+2026-10-19 17:59:47.469175: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 17:59:47.754552: lr: 0.000607 
+2026-10-19 17:59:47.754838: This epoch took 235.917386 s
+ 
+2026-10-19 17:59:47.754929: 
+epoch:  426 
+2026-10-19 18:03:32.036569: train loss : -0.8405 
+2026-10-19 18:03:37.389983: validation loss: -0.7404 
+2026-10-19 18:03:37.391000: Average global foreground Dice: [np.float32(0.9463), np.float32(0.7768), np.float32(0.8805), np.float32(0.8954), np.float32(0.8323), np.float32(0.9385), np.float32(0.893), np.float32(0.7647), np.float32(0.0), np.float32(0.5641), np.float32(0.7349), np.float32(0.8327), np.float32(0.7232), np.float32(0.5767), np.float32(0.0), np.float32(0.0), np.float32(0.8351), np.float32(0.6734), np.float32(0.841), np.float32(0.7151), np.float32(0.4187), np.float32(0.7763), np.float32(0.9396), np.float32(0.9361), np.float32(0.6647), np.float32(0.6954), np.float32(0.3682), np.float32(0.8365), np.float32(0.6812), np.float32(0.8019), np.float32(0.0), np.float32(0.0), np.float32(0.7296), np.float32(0.6557), np.float32(0.9636), np.float32(0.9691)] 
+2026-10-19 18:03:37.391159: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 18:03:37.662160: lr: 0.000606 
+2026-10-19 18:03:37.662363: This epoch took 229.907367 s
+ 
+2026-10-19 18:03:37.662425: 
+epoch:  427 
+2026-10-19 18:07:18.011655: train loss : -0.8362 
+2026-10-19 18:07:23.342504: validation loss: -0.7411 
+2026-10-19 18:07:23.343531: Average global foreground Dice: [np.float32(0.943), np.float32(0.7301), np.float32(0.8709), np.float32(0.893), np.float32(0.7997), np.float32(0.9335), np.float32(0.8768), np.float32(0.586), np.float32(0.0), np.float32(0.5022), np.float32(0.7551), np.float32(0.8411), np.float32(0.7666), np.float32(0.644), np.float32(0.0), np.float32(0.0), np.float32(0.8169), np.float32(0.623), np.float32(0.8222), np.float32(0.6895), np.float32(0.3027), np.float32(0.7721), np.float32(0.9317), np.float32(0.9267), np.float32(0.6118), np.float32(0.682), np.float32(0.372), np.float32(0.812), np.float32(0.6371), np.float32(0.7649), np.float32(0.0), np.float32(0.0), np.float32(0.7329), np.float32(0.6944), np.float32(0.9567), np.float32(0.9669)] 
+2026-10-19 18:07:23.343765: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 18:07:23.636292: lr: 0.000605 
+2026-10-19 18:07:23.636606: This epoch took 225.974120 s
+ 
+2026-10-19 18:07:23.636711: 
+epoch:  428 
+2026-10-19 18:11:23.089777: train loss : -0.8349 
+2026-10-19 18:11:28.431371: validation loss: -0.7427 
+2026-10-19 18:11:28.432384: Average global foreground Dice: [np.float32(0.9416), np.float32(0.7436), np.float32(0.8628), np.float32(0.8886), np.float32(0.7869), np.float32(0.9319), np.float32(0.8953), np.float32(0.7113), np.float32(0.0), np.float32(0.5599), np.float32(0.7738), np.float32(0.8453), np.float32(0.7725), np.float32(0.6838), np.float32(0.0), np.float32(0.0), np.float32(0.8211), np.float32(0.669), np.float32(0.8365), np.float32(0.7159), np.float32(0.2791), np.float32(0.8044), np.float32(0.9278), np.float32(0.9182), np.float32(0.6549), np.float32(0.6914), np.float32(0.3641), np.float32(0.8676), np.float32(0.6493), np.float32(0.7862), np.float32(0.0), np.float32(0.0), np.float32(0.7322), np.float32(0.6616), np.float32(0.941), np.float32(0.969)] 
+2026-10-19 18:11:28.432610: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 18:11:28.706369: lr: 0.000604 
+2026-10-19 18:11:28.706706: This epoch took 245.069924 s
+ 
+2026-10-19 18:11:28.706829: 
+epoch:  429 
+2026-10-19 18:15:30.471897: train loss : -0.8416 
+2026-10-19 18:15:35.814687: validation loss: -0.7271 
+2026-10-19 18:15:35.815529: Average global foreground Dice: [np.float32(0.9419), np.float32(0.7182), np.float32(0.8759), np.float32(0.8813), np.float32(0.7796), np.float32(0.9408), np.float32(0.8894), np.float32(0.5886), np.float32(0.0), np.float32(0.5866), np.float32(0.7391), np.float32(0.8111), np.float32(0.6576), np.float32(0.6272), np.float32(0.0), np.float32(0.0), np.float32(0.8237), np.float32(0.6793), np.float32(0.8362), np.float32(0.7201), np.float32(0.3875), np.float32(0.7881), np.float32(0.9363), np.float32(0.9261), np.float32(0.6581), np.float32(0.7021), np.float32(0.3697), np.float32(0.8639), np.float32(0.6334), np.float32(0.763), np.float32(0.0), np.float32(0.0), np.float32(0.7408), np.float32(0.6621), np.float32(0.9534), np.float32(0.9699)] 
+2026-10-19 18:15:35.815904: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 18:15:36.097060: lr: 0.000603 
+2026-10-19 18:15:36.097395: This epoch took 247.390504 s
+ 
+2026-10-19 18:15:36.097605: 
+epoch:  430 
+2026-10-19 18:19:23.016157: train loss : -0.8383 
+2026-10-19 18:19:28.368494: validation loss: -0.7471 
+2026-10-19 18:19:28.369572: Average global foreground Dice: [np.float32(0.9416), np.float32(0.7221), np.float32(0.8686), np.float32(0.8879), np.float32(0.8032), np.float32(0.9385), np.float32(0.8813), np.float32(0.5867), np.float32(0.0), np.float32(0.5731), np.float32(0.7478), np.float32(0.8348), np.float32(0.7219), np.float32(0.6503), np.float32(0.0108), np.float32(0.0), np.float32(0.8221), np.float32(0.6574), np.float32(0.8272), np.float32(0.7176), np.float32(0.31), np.float32(0.8076), np.float32(0.9319), np.float32(0.9249), np.float32(0.6186), np.float32(0.6665), np.float32(0.3792), np.float32(0.8187), np.float32(0.6367), np.float32(0.7842), np.float32(0.0), np.float32(0.0), np.float32(0.7469), np.float32(0.6794), np.float32(0.9567), np.float32(0.9689)] 
+2026-10-19 18:19:28.370134: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 18:19:28.659544: lr: 0.000602 
+2026-10-19 18:19:28.659989: This epoch took 232.562290 s
+ 
+2026-10-19 18:19:28.660364: 
+epoch:  431 
+2026-10-19 18:23:24.390877: train loss : -0.8371 
+2026-10-19 18:23:29.729803: validation loss: -0.7252 
+2026-10-19 18:23:29.730860: Average global foreground Dice: [np.float32(0.9381), np.float32(0.7387), np.float32(0.8635), np.float32(0.8678), np.float32(0.791), np.float32(0.9364), np.float32(0.896), np.float32(0.763), np.float32(0.0), np.float32(0.5563), np.float32(0.7385), np.float32(0.8338), np.float32(0.707), np.float32(0.5884), np.float32(0.0093), np.float32(0.0), np.float32(0.8191), np.float32(0.6521), np.float32(0.8428), np.float32(0.7009), np.float32(0.338), np.float32(0.7698), np.float32(0.9157), np.float32(0.9091), np.float32(0.6302), np.float32(0.6754), np.float32(0.4758), np.float32(0.0096), np.float32(0.6608), np.float32(0.7259), np.float32(0.0), np.float32(0.0), np.float32(0.6906), np.float32(0.6327), np.float32(0.9522), np.float32(0.9686)] 
+2026-10-19 18:23:29.731068: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 18:23:30.012137: lr: 0.000601 
+2026-10-19 18:23:30.012589: This epoch took 241.351954 s
+ 
+2026-10-19 18:23:30.012883: 
+epoch:  432 
+2026-10-19 18:27:34.684511: train loss : -0.8332 
+2026-10-19 18:27:40.021849: validation loss: -0.7318 
+2026-10-19 18:27:40.023185: Average global foreground Dice: [np.float32(0.9358), np.float32(0.6999), np.float32(0.859), np.float32(0.8916), np.float32(0.7919), np.float32(0.9378), np.float32(0.8932), np.float32(0.6362), np.float32(0.0), np.float32(0.4534), np.float32(0.7478), np.float32(0.8259), np.float32(0.7107), np.float32(0.6406), np.float32(0.0), np.float32(0.0), np.float32(0.8203), np.float32(0.6535), np.float32(0.8314), np.float32(0.7098), np.float32(0.2951), np.float32(0.7769), np.float32(0.9282), np.float32(0.9208), np.float32(0.6078), np.float32(0.7058), np.float32(0.4189), np.float32(0.8127), np.float32(0.5793), np.float32(0.7282), np.float32(0.0), np.float32(0.0), np.float32(0.7542), np.float32(0.6355), np.float32(0.9523), np.float32(0.9682)] 
+2026-10-19 18:27:40.023594: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 18:27:40.307034: lr: 0.0006 
+2026-10-19 18:27:40.307246: This epoch took 250.294161 s
+ 
+2026-10-19 18:27:40.307364: 
+epoch:  433 
+2026-10-19 18:31:29.472657: train loss : -0.8391 
+2026-10-19 18:31:34.799322: validation loss: -0.7396 
+2026-10-19 18:31:34.800115: Average global foreground Dice: [np.float32(0.9438), np.float32(0.7491), np.float32(0.8664), np.float32(0.8836), np.float32(0.7907), np.float32(0.9345), np.float32(0.8868), np.float32(0.7217), np.float32(0.0), np.float32(0.5634), np.float32(0.7598), np.float32(0.8273), np.float32(0.7091), np.float32(0.6373), np.float32(0.0), np.float32(0.0), np.float32(0.818), np.float32(0.6294), np.float32(0.8176), np.float32(0.6831), np.float32(0.3446), np.float32(0.7924), np.float32(0.931), np.float32(0.9242), np.float32(0.6061), np.float32(0.6647), np.float32(0.4102), np.float32(0.8164), np.float32(0.6502), np.float32(0.7311), np.float32(0.0), np.float32(0.0), np.float32(0.7391), np.float32(0.6464), np.float32(0.9487), np.float32(0.9678)] 
+2026-10-19 18:31:34.800285: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 18:31:35.091697: lr: 0.000599 
+2026-10-19 18:31:35.092019: This epoch took 234.784485 s
+ 
+2026-10-19 18:31:35.092223: 
+epoch:  434 
+2026-10-19 18:35:33.223345: train loss : -0.8321 
+2026-10-19 18:35:38.573946: validation loss: -0.7270 
+2026-10-19 18:35:38.575024: Average global foreground Dice: [np.float32(0.9452), np.float32(0.7598), np.float32(0.8728), np.float32(0.8941), np.float32(0.8148), np.float32(0.9384), np.float32(0.889), np.float32(0.7648), np.float32(0.0), np.float32(0.4651), np.float32(0.7528), np.float32(0.8172), np.float32(0.7366), np.float32(0.6336), np.float32(0.0), np.float32(0.0), np.float32(0.8272), np.float32(0.653), np.float32(0.8402), np.float32(0.7166), np.float32(0.3778), np.float32(0.7987), np.float32(0.9321), np.float32(0.9161), np.float32(0.5911), np.float32(0.6667), np.float32(0.3591), np.float32(0.7104), np.float32(0.6181), np.float32(0.7462), np.float32(0.0), np.float32(0.0), np.float32(0.7078), np.float32(0.6543), np.float32(0.9582), np.float32(0.9706)] 
+2026-10-19 18:35:38.575437: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 18:35:38.873681: lr: 0.000598 
+2026-10-19 18:35:38.874048: This epoch took 243.781750 s
+ 
+2026-10-19 18:35:38.874320: 
+epoch:  435 
+2026-10-19 18:39:27.854810: train loss : -0.8370 
+2026-10-19 18:39:33.194761: validation loss: -0.7300 
+2026-10-19 18:39:33.195674: Average global foreground Dice: [np.float32(0.9416), np.float32(0.7394), np.float32(0.8714), np.float32(0.8803), np.float32(0.7914), np.float32(0.9397), np.float32(0.8844), np.float32(0.8142), np.float32(0.0), np.float32(0.5037), np.float32(0.7615), np.float32(0.8489), np.float32(0.7467), np.float32(0.6685), np.float32(0.0), np.float32(0.0), np.float32(0.8126), np.float32(0.6297), np.float32(0.8319), np.float32(0.6877), np.float32(0.2987), np.float32(0.7707), np.float32(0.9299), np.float32(0.9212), np.float32(0.6177), np.float32(0.6986), np.float32(0.4105), np.float32(0.8669), np.float32(0.5595), np.float32(0.7464), np.float32(0.0), np.float32(0.0), np.float32(0.7316), np.float32(0.6499), np.float32(0.9472), np.float32(0.9682)] 
+2026-10-19 18:39:33.195844: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 18:39:33.488611: lr: 0.000597 
+2026-10-19 18:39:33.488933: This epoch took 234.614491 s
+ 
+2026-10-19 18:39:33.489038: 
+epoch:  436 
+2026-10-19 18:43:56.281233: train loss : -0.8351 
+2026-10-19 18:44:01.606502: validation loss: -0.7278 
+2026-10-19 18:44:01.607516: Average global foreground Dice: [np.float32(0.9377), np.float32(0.7357), np.float32(0.8698), np.float32(0.8836), np.float32(0.8046), np.float32(0.938), np.float32(0.8861), np.float32(0.7852), np.float32(0.0), np.float32(0.4717), np.float32(0.7738), np.float32(0.8526), np.float32(0.7484), np.float32(0.6685), np.float32(0.0), np.float32(0.0), np.float32(0.8157), np.float32(0.6349), np.float32(0.84), np.float32(0.688), np.float32(0.2816), np.float32(0.7954), np.float32(0.9248), np.float32(0.9214), np.float32(0.6594), np.float32(0.6935), np.float32(0.3806), np.float32(0.8475), np.float32(0.5603), np.float32(0.7697), np.float32(0.0), np.float32(0.0), np.float32(0.7534), np.float32(0.6985), np.float32(0.9553), np.float32(0.9691)] 
+2026-10-19 18:44:01.607840: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 18:44:01.897490: lr: 0.000596 
+2026-10-19 18:44:01.897930: This epoch took 268.408835 s
+ 
+2026-10-19 18:44:01.898223: 
+epoch:  437 
+2026-10-19 18:47:47.998730: train loss : -0.8371 
+2026-10-19 18:47:53.335280: validation loss: -0.7356 
+2026-10-19 18:47:53.336354: Average global foreground Dice: [np.float32(0.936), np.float32(0.7523), np.float32(0.884), np.float32(0.9021), np.float32(0.8272), np.float32(0.9375), np.float32(0.8834), np.float32(0.7492), np.float32(0.0), np.float32(0.6209), np.float32(0.767), np.float32(0.847), np.float32(0.7106), np.float32(0.596), np.float32(0.0), np.float32(0.0), np.float32(0.8301), np.float32(0.6735), np.float32(0.8509), np.float32(0.7384), np.float32(0.3172), np.float32(0.8086), np.float32(0.9354), np.float32(0.9278), np.float32(0.691), np.float32(0.7027), np.float32(0.3876), np.float32(0.8588), np.float32(0.6116), np.float32(0.7943), np.float32(0.0), np.float32(0.0), np.float32(0.7339), np.float32(0.686), np.float32(0.9559), np.float32(0.9685)] 
+2026-10-19 18:47:53.336535: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 18:47:53.622254: lr: 0.000595 
+2026-10-19 18:47:53.622479: This epoch took 231.724047 s
+ 
+2026-10-19 18:47:53.622549: 
+epoch:  438 
+2026-10-19 18:51:38.544649: train loss : -0.8400 
+2026-10-19 18:51:43.891302: validation loss: -0.7353 
+2026-10-19 18:51:43.892378: Average global foreground Dice: [np.float32(0.943), np.float32(0.7735), np.float32(0.8626), np.float32(0.8774), np.float32(0.8225), np.float32(0.9258), np.float32(0.8918), np.float32(0.7514), np.float32(0.0), np.float32(0.5572), np.float32(0.7617), np.float32(0.8277), np.float32(0.746), np.float32(0.6515), np.float32(0.0), np.float32(0.0), np.float32(0.8206), np.float32(0.6341), np.float32(0.8384), np.float32(0.7011), np.float32(0.316), np.float32(0.8022), np.float32(0.9272), np.float32(0.9185), np.float32(0.6453), np.float32(0.657), np.float32(0.4015), np.float32(0.7704), np.float32(0.679), np.float32(0.7852), np.float32(0.0), np.float32(0.0), np.float32(0.7218), np.float32(0.6714), np.float32(0.9558), np.float32(0.968)] 
+2026-10-19 18:51:43.892628: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 18:51:44.194807: lr: 0.000594 
+2026-10-19 18:51:44.195088: This epoch took 230.572475 s
+ 
+2026-10-19 18:51:44.195179: 
+epoch:  439 
+2026-10-19 18:55:29.453444: train loss : -0.8422 
+2026-10-19 18:55:34.798624: validation loss: -0.7289 
+2026-10-19 18:55:34.799706: Average global foreground Dice: [np.float32(0.9445), np.float32(0.7189), np.float32(0.8733), np.float32(0.89), np.float32(0.8149), np.float32(0.9268), np.float32(0.8827), np.float32(0.5276), np.float32(0.0), np.float32(0.4417), np.float32(0.7519), np.float32(0.841), np.float32(0.7274), np.float32(0.6248), np.float32(0.0), np.float32(0.0), np.float32(0.8212), np.float32(0.6438), np.float32(0.846), np.float32(0.707), np.float32(0.2992), np.float32(0.8156), np.float32(0.9326), np.float32(0.9335), np.float32(0.6428), np.float32(0.687), np.float32(0.4076), np.float32(0.828), np.float32(0.6548), np.float32(0.813), np.float32(0.0), np.float32(0.0), np.float32(0.7303), np.float32(0.6791), np.float32(0.9531), np.float32(0.9693)] 
+2026-10-19 18:55:34.800008: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 18:55:35.084375: lr: 0.000593 
+2026-10-19 18:55:35.084643: This epoch took 230.889400 s
+ 
+2026-10-19 18:55:35.084737: 
+epoch:  440 
+2026-10-19 18:58:57.835937: train loss : -0.8389 
+2026-10-19 18:59:03.187672: validation loss: -0.7345 
+2026-10-19 18:59:03.188781: Average global foreground Dice: [np.float32(0.9402), np.float32(0.7442), np.float32(0.8775), np.float32(0.8871), np.float32(0.806), np.float32(0.928), np.float32(0.904), np.float32(0.7475), np.float32(0.0), np.float32(0.5815), np.float32(0.7562), np.float32(0.8514), np.float32(0.7328), np.float32(0.6339), np.float32(0.0), np.float32(0.0), np.float32(0.8221), np.float32(0.6703), np.float32(0.8439), np.float32(0.7047), np.float32(0.3404), np.float32(0.7843), np.float32(0.9274), np.float32(0.9209), np.float32(0.6245), np.float32(0.7058), np.float32(0.4185), np.float32(0.8608), np.float32(0.623), np.float32(0.7213), np.float32(0.0), np.float32(0.0), np.float32(0.7168), np.float32(0.664), np.float32(0.9575), np.float32(0.9678)] 
+2026-10-19 18:59:03.189122: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 18:59:03.473687: lr: 0.000592 
+2026-10-19 18:59:03.473947: This epoch took 208.389142 s
+ 
+2026-10-19 18:59:03.474030: 
+epoch:  441 
+2026-10-19 19:03:02.489229: train loss : -0.8393 
+2026-10-19 19:03:07.829172: validation loss: -0.7335 
+2026-10-19 19:03:07.830238: Average global foreground Dice: [np.float32(0.9368), np.float32(0.7447), np.float32(0.8786), np.float32(0.8896), np.float32(0.8266), np.float32(0.9342), np.float32(0.8887), np.float32(0.5379), np.float32(0.0), np.float32(0.4933), np.float32(0.7469), np.float32(0.8387), np.float32(0.7266), np.float32(0.5965), np.float32(0.0), np.float32(0.0), np.float32(0.8239), np.float32(0.6645), np.float32(0.8355), np.float32(0.6981), np.float32(0.3471), np.float32(0.8007), np.float32(0.9249), np.float32(0.9245), np.float32(0.6349), np.float32(0.6991), np.float32(0.4138), np.float32(0.8222), np.float32(0.6376), np.float32(0.7815), np.float32(0.0), np.float32(0.0), np.float32(0.7288), np.float32(0.667), np.float32(0.9553), np.float32(0.9684)] 
+2026-10-19 19:03:07.830489: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 19:03:08.114974: lr: 0.000592 
+2026-10-19 19:03:08.115199: This epoch took 244.641104 s
+ 
+2026-10-19 19:03:08.115352: 
+epoch:  442 
+2026-10-19 19:07:17.953102: train loss : -0.8386 
+2026-10-19 19:07:23.292591: validation loss: -0.7266 
+2026-10-19 19:07:23.293567: Average global foreground Dice: [np.float32(0.9431), np.float32(0.7267), np.float32(0.8896), np.float32(0.8899), np.float32(0.813), np.float32(0.9362), np.float32(0.8956), np.float32(0.6274), np.float32(0.0), np.float32(0.5712), np.float32(0.7561), np.float32(0.8387), np.float32(0.7247), np.float32(0.6122), np.float32(0.0), np.float32(0.0), np.float32(0.8172), np.float32(0.6237), np.float32(0.8392), np.float32(0.694), np.float32(0.323), np.float32(0.782), np.float32(0.9352), np.float32(0.938), np.float32(0.6462), np.float32(0.7043), np.float32(0.4256), np.float32(0.8276), np.float32(0.6024), np.float32(0.7756), np.float32(0.0), np.float32(0.0), np.float32(0.7294), np.float32(0.6795), np.float32(0.9587), np.float32(0.9692)] 
+2026-10-19 19:07:23.293897: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 19:07:23.604508: lr: 0.000591 
+2026-10-19 19:07:23.604774: This epoch took 255.489351 s
+ 
+2026-10-19 19:07:23.604854: 
+epoch:  443 
+2026-10-19 19:11:27.623491: train loss : -0.8316 
+2026-10-19 19:11:32.962571: validation loss: -0.7146 
+2026-10-19 19:11:32.963452: Average global foreground Dice: [np.float32(0.9401), np.float32(0.7566), np.float32(0.8631), np.float32(0.8865), np.float32(0.8198), np.float32(0.9361), np.float32(0.9014), np.float32(0.5543), np.float32(0.0), np.float32(0.5511), np.float32(0.7531), np.float32(0.7899), np.float32(0.7214), np.float32(0.5502), np.float32(0.0022), np.float32(0.0), np.float32(0.833), np.float32(0.6507), np.float32(0.8433), np.float32(0.7127), np.float32(0.5042), np.float32(0.7806), np.float32(0.9324), np.float32(0.9264), np.float32(0.636), np.float32(0.6735), np.float32(0.4041), np.float32(0.7274), np.float32(0.6876), np.float32(0.7431), np.float32(0.0), np.float32(0.0), np.float32(0.7443), np.float32(0.6729), np.float32(0.9488), np.float32(0.9685)] 
+2026-10-19 19:11:32.963847: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 19:11:33.240240: lr: 0.00059 
+2026-10-19 19:11:33.240519: This epoch took 249.635608 s
+ 
+2026-10-19 19:11:33.240617: 
+epoch:  444 
+2026-10-19 19:15:13.057362: train loss : -0.8347 
+2026-10-19 19:15:18.394669: validation loss: -0.7384 
+2026-10-19 19:15:18.395894: Average global foreground Dice: [np.float32(0.9423), np.float32(0.725), np.float32(0.8798), np.float32(0.8949), np.float32(0.8082), np.float32(0.9385), np.float32(0.889), np.float32(0.4947), np.float32(0.0), np.float32(0.523), np.float32(0.7444), np.float32(0.8433), np.float32(0.7215), np.float32(0.6055), np.float32(0.0), np.float32(0.0), np.float32(0.8218), np.float32(0.6371), np.float32(0.843), np.float32(0.7106), np.float32(0.3199), np.float32(0.7796), np.float32(0.9332), np.float32(0.91), np.float32(0.6517), np.float32(0.6864), np.float32(0.3885), np.float32(0.8099), np.float32(0.6389), np.float32(0.7779), np.float32(0.0), np.float32(0.0), np.float32(0.7575), np.float32(0.6732), np.float32(0.9558), np.float32(0.9679)] 
+2026-10-19 19:15:18.396231: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 19:15:18.679810: lr: 0.000589 
+2026-10-19 19:15:18.680082: This epoch took 225.439397 s
+ 
+2026-10-19 19:15:18.680592: 
+epoch:  445 
+2026-10-19 19:19:17.036923: train loss : -0.8336 
+2026-10-19 19:19:22.380668: validation loss: -0.7575 
+2026-10-19 19:19:22.381715: Average global foreground Dice: [np.float32(0.9409), np.float32(0.7805), np.float32(0.8726), np.float32(0.899), np.float32(0.8315), np.float32(0.9351), np.float32(0.8856), np.float32(0.7028), np.float32(0.0), np.float32(0.577), np.float32(0.777), np.float32(0.8544), np.float32(0.7453), np.float32(0.658), np.float32(0.0), np.float32(0.0), np.float32(0.8259), np.float32(0.655), np.float32(0.8365), np.float32(0.7003), np.float32(0.3767), np.float32(0.7902), np.float32(0.9117), np.float32(0.9027), np.float32(0.6525), np.float32(0.6669), np.float32(0.4532), np.float32(0.809), np.float32(0.6921), np.float32(0.7918), np.float32(0.0), np.float32(0.0), np.float32(0.7488), np.float32(0.6506), np.float32(0.9566), np.float32(0.9663)] 
+2026-10-19 19:19:22.381855: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 19:19:22.668457: lr: 0.000588 
+2026-10-19 19:19:22.668951: This epoch took 243.988028 s
+ 
+2026-10-19 19:19:22.669254: 
+epoch:  446 
+2026-10-19 19:23:06.883683: train loss : -0.8415 
+2026-10-19 19:23:12.218566: validation loss: -0.7285 
+2026-10-19 19:23:12.219596: Average global foreground Dice: [np.float32(0.9403), np.float32(0.7436), np.float32(0.8695), np.float32(0.8908), np.float32(0.8071), np.float32(0.9372), np.float32(0.8931), np.float32(0.6484), np.float32(0.0), np.float32(0.3781), np.float32(0.7393), np.float32(0.8211), np.float32(0.7341), np.float32(0.6355), np.float32(0.0), np.float32(0.0), np.float32(0.8289), np.float32(0.6672), np.float32(0.8479), np.float32(0.7227), np.float32(0.3087), np.float32(0.8079), np.float32(0.9298), np.float32(0.9227), np.float32(0.6131), np.float32(0.6637), np.float32(0.3928), np.float32(0.8433), np.float32(0.628), np.float32(0.7612), np.float32(0.0), np.float32(0.0), np.float32(0.7378), np.float32(0.6629), np.float32(0.9574), np.float32(0.9702)] 
+2026-10-19 19:23:12.219749: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 19:23:12.505558: lr: 0.000587 
+2026-10-19 19:23:12.505997: This epoch took 229.836353 s
+ 
+2026-10-19 19:23:12.506174: 
+epoch:  447 
+2026-10-19 19:27:04.063797: train loss : -0.8363 
+2026-10-19 19:27:09.426682: validation loss: -0.7225 
+2026-10-19 19:27:09.427778: Average global foreground Dice: [np.float32(0.9417), np.float32(0.7294), np.float32(0.8717), np.float32(0.8977), np.float32(0.8168), np.float32(0.9383), np.float32(0.8886), np.float32(0.6846), np.float32(0.0), np.float32(0.5536), np.float32(0.7708), np.float32(0.8655), np.float32(0.6918), np.float32(0.606), np.float32(0.0007), np.float32(0.0), np.float32(0.835), np.float32(0.6581), np.float32(0.8458), np.float32(0.7162), np.float32(0.4408), np.float32(0.8049), np.float32(0.9329), np.float32(0.9286), np.float32(0.631), np.float32(0.6852), np.float32(0.4033), np.float32(0.8587), np.float32(0.6417), np.float32(0.7573), np.float32(0.0), np.float32(0.0), np.float32(0.7433), np.float32(0.6955), np.float32(0.9546), np.float32(0.9701)] 
+2026-10-19 19:27:09.428190: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 19:27:09.724323: lr: 0.000586 
+2026-10-19 19:27:09.724572: This epoch took 237.218318 s
+ 
+2026-10-19 19:27:09.724658: 
+epoch:  448 
+2026-10-19 19:31:07.356610: train loss : -0.8416 
+2026-10-19 19:31:12.697045: validation loss: -0.7289 
+2026-10-19 19:31:12.698334: Average global foreground Dice: [np.float32(0.9415), np.float32(0.7379), np.float32(0.8691), np.float32(0.8796), np.float32(0.7906), np.float32(0.9348), np.float32(0.8883), np.float32(0.5083), np.float32(0.0), np.float32(0.524), np.float32(0.7399), np.float32(0.8139), np.float32(0.7333), np.float32(0.6262), np.float32(0.0), np.float32(0.0), np.float32(0.8328), np.float32(0.6705), np.float32(0.8479), np.float32(0.7233), np.float32(0.3833), np.float32(0.7887), np.float32(0.9326), np.float32(0.9238), np.float32(0.6335), np.float32(0.6878), np.float32(0.4288), np.float32(0.849), np.float32(0.6168), np.float32(0.7913), np.float32(0.0), np.float32(0.0), np.float32(0.7692), np.float32(0.6837), np.float32(0.9524), np.float32(0.97)] 
+2026-10-19 19:31:12.698627: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 19:31:12.978245: lr: 0.000585 
+2026-10-19 19:31:12.978477: This epoch took 243.253764 s
+ 
+2026-10-19 19:31:12.978567: 
+epoch:  449 
+2026-10-19 19:35:15.967521: train loss : -0.8357 
+2026-10-19 19:35:21.310163: validation loss: -0.7479 
+2026-10-19 19:35:21.311247: Average global foreground Dice: [np.float32(0.9418), np.float32(0.7593), np.float32(0.8871), np.float32(0.8905), np.float32(0.829), np.float32(0.932), np.float32(0.8969), np.float32(0.613), np.float32(0.0), np.float32(0.5375), np.float32(0.7467), np.float32(0.8397), np.float32(0.705), np.float32(0.6161), np.float32(0.0), np.float32(0.0), np.float32(0.8338), np.float32(0.6605), np.float32(0.8486), np.float32(0.7077), np.float32(0.3749), np.float32(0.7894), np.float32(0.936), np.float32(0.9337), np.float32(0.6604), np.float32(0.7028), np.float32(0.4165), np.float32(0.8136), np.float32(0.6368), np.float32(0.7941), np.float32(0.0), np.float32(0.0), np.float32(0.7395), np.float32(0.6814), np.float32(0.9598), np.float32(0.9691)] 
+2026-10-19 19:35:21.311735: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 19:35:21.596309: lr: 0.000584 
+2026-10-19 19:35:21.596528: saving scheduled checkpoint file... 
+2026-10-19 19:35:21.604660: saving checkpoint... 
+2026-10-19 19:35:21.737331: done, saving took 0.14 seconds 
+2026-10-19 19:35:21.738738: done 
+2026-10-19 19:35:21.738992: This epoch took 248.760369 s
+ 
+2026-10-19 19:35:21.739077: 
+epoch:  450 
+2026-10-19 19:38:50.600511: train loss : -0.8430 
+2026-10-19 19:38:55.938077: validation loss: -0.7303 
+2026-10-19 19:38:55.939113: Average global foreground Dice: [np.float32(0.9318), np.float32(0.7258), np.float32(0.872), np.float32(0.8796), np.float32(0.7911), np.float32(0.9343), np.float32(0.8962), np.float32(0.6695), np.float32(0.0), np.float32(0.2453), np.float32(0.746), np.float32(0.8303), np.float32(0.7376), np.float32(0.6624), np.float32(0.0), np.float32(0.0), np.float32(0.8207), np.float32(0.5896), np.float32(0.8365), np.float32(0.709), np.float32(0.3461), np.float32(0.7597), np.float32(0.9142), np.float32(0.9084), np.float32(0.6391), np.float32(0.7084), np.float32(0.3994), np.float32(0.8681), np.float32(0.6186), np.float32(0.7678), np.float32(0.0), np.float32(0.0), np.float32(0.7421), np.float32(0.6787), np.float32(0.9496), np.float32(0.967)] 
+2026-10-19 19:38:55.939698: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 19:38:56.249527: lr: 0.000583 
+2026-10-19 19:38:56.249824: This epoch took 214.510585 s
+ 
+2026-10-19 19:38:56.249928: 
+epoch:  451 
+2026-10-19 19:43:02.893428: train loss : -0.8332 
+2026-10-19 19:43:08.223719: validation loss: -0.7379 
+2026-10-19 19:43:08.224705: Average global foreground Dice: [np.float32(0.9454), np.float32(0.7563), np.float32(0.8755), np.float32(0.8943), np.float32(0.8209), np.float32(0.9391), np.float32(0.9018), np.float32(0.6753), np.float32(0.0), np.float32(0.3386), np.float32(0.7559), np.float32(0.8505), np.float32(0.7581), np.float32(0.6188), np.float32(0.0), np.float32(0.0), np.float32(0.8165), np.float32(0.637), np.float32(0.8371), np.float32(0.6996), np.float32(0.3214), np.float32(0.7719), np.float32(0.9337), np.float32(0.9211), np.float32(0.623), np.float32(0.6798), np.float32(0.3956), np.float32(0.8411), np.float32(0.6299), np.float32(0.798), np.float32(0.0), np.float32(0.0), np.float32(0.7451), np.float32(0.6653), np.float32(0.953), np.float32(0.9668)] 
+2026-10-19 19:43:08.225140: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 19:43:08.538536: lr: 0.000582 
+2026-10-19 19:43:08.539026: This epoch took 252.289033 s
+ 
+2026-10-19 19:43:08.539267: 
+epoch:  452 
+2026-10-19 19:47:01.656309: train loss : -0.8329 
+2026-10-19 19:47:07.044017: validation loss: -0.7209 
+2026-10-19 19:47:07.045222: Average global foreground Dice: [np.float32(0.9452), np.float32(0.7396), np.float32(0.8823), np.float32(0.9024), np.float32(0.8213), np.float32(0.9316), np.float32(0.8865), np.float32(0.6955), np.float32(0.0), np.float32(0.4991), np.float32(0.75), np.float32(0.8574), np.float32(0.6629), np.float32(0.5774), np.float32(0.0), np.float32(0.0), np.float32(0.814), np.float32(0.6373), np.float32(0.8418), np.float32(0.7131), np.float32(0.3544), np.float32(0.8014), np.float32(0.9244), np.float32(0.9171), np.float32(0.6279), np.float32(0.68), np.float32(0.3605), np.float32(0.8385), np.float32(0.6153), np.float32(0.7868), np.float32(0.0), np.float32(0.0), np.float32(0.7445), np.float32(0.6603), np.float32(0.96), np.float32(0.9709)] 
+2026-10-19 19:47:07.045651: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 19:47:07.339651: lr: 0.000581 
+2026-10-19 19:47:07.339954: This epoch took 238.800586 s
+ 
+2026-10-19 19:47:07.340203: 
+epoch:  453 
+2026-10-19 19:51:40.401189: train loss : -0.8287 
+2026-10-19 19:51:45.743676: validation loss: -0.7335 
+2026-10-19 19:51:45.744660: Average global foreground Dice: [np.float32(0.9396), np.float32(0.7385), np.float32(0.8685), np.float32(0.8763), np.float32(0.8081), np.float32(0.9221), np.float32(0.8894), np.float32(0.3529), np.float32(0.0), np.float32(0.3875), np.float32(0.7568), np.float32(0.827), np.float32(0.7279), np.float32(0.6036), np.float32(0.0), np.float32(0.0), np.float32(0.8086), np.float32(0.6152), np.float32(0.8227), np.float32(0.6648), np.float32(0.2717), np.float32(0.8092), np.float32(0.9336), np.float32(0.928), np.float32(0.5877), np.float32(0.647), np.float32(0.3598), np.float32(0.778), np.float32(0.675), np.float32(0.7704), np.float32(0.0), np.float32(0.0), np.float32(0.7312), np.float32(0.6269), np.float32(0.953), np.float32(0.964)] 
+2026-10-19 19:51:45.744831: (interpret this as an estimate for the Dice of the different classes. This is not exact.) 
+2026-10-19 19:51:46.037561: lr: 0.00058 
+2026-10-19 19:51:46.037885: This epoch took 278.697600 s
+ 
+2026-10-19 19:51:46.038002: 
+epoch:  454