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MedNeXt_Large/fold_0_CT/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_L_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/debug.json

@@ -1,28 +1,28 @@
 {
-    "all_tr_losses": "[]",
-    "all_val_eval_metrics": "[]",
-    "all_val_losses": "[]",
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+    "all_val_losses": "[np.float32(-0.07470091), np.float32(-0.1155705), np.float32(-0.19333363), np.float32(-0.27809945), np.float32(-0.37054774), np.float32(-0.3565181), np.float32(-0.3831776), np.float32(-0.401925), np.float32(-0.38338625), np.float32(-0.36536282), np.float32(-0.45441592), np.float32(-0.37744793), np.float32(-0.3529129), np.float32(-0.2656958), np.float32(-0.37089065), np.float32(-0.463354), np.float32(-0.37575164), np.float32(-0.51616085), np.float32(-0.52158797), np.float32(-0.49252146), np.float32(-0.46345484), np.float32(-0.44432026), np.float32(-0.3875055), np.float32(-0.29651347), np.float32(-0.374561), np.float32(-0.44172478), np.float32(-0.3020468), np.float32(-0.3249737), np.float32(-0.33035675), np.float32(-0.48948795), np.float32(-0.41371545), np.float32(-0.43393955), np.float32(-0.46594632), np.float32(-0.5379311), np.float32(-0.4374967), np.float32(-0.46398762), np.float32(-0.40548974), np.float32(-0.26895827), np.float32(-0.5160663), np.float32(-0.4170287), np.float32(-0.3874871), np.float32(-0.56852984), np.float32(-0.20573968), np.float32(-0.4403778), np.float32(-0.28382945), np.float32(-0.4249569), np.float32(-0.4226168), np.float32(-0.4591214), np.float32(-0.36560845), np.float32(-0.43757272), np.float32(-0.4334856), np.float32(-0.44014493), np.float32(-0.45037532), np.float32(-0.45998502), np.float32(-0.4603461), np.float32(-0.34373438), np.float32(-0.46866146), np.float32(-0.44739568), np.float32(-0.52187514), np.float32(-0.46080753), np.float32(-0.478531), np.float32(-0.53193355), np.float32(-0.5221857), np.float32(-0.4397172), np.float32(-0.50099033), np.float32(-0.544881), np.float32(-0.48568553), np.float32(-0.48982775), np.float32(-0.45025373), np.float32(-0.5496275), np.float32(-0.49164483), np.float32(-0.4180044), np.float32(-0.48074684), np.float32(-0.20900002), np.float32(-0.49134067), np.float32(-0.43336174), np.float32(-0.43484515), np.float32(-0.3493756), np.float32(-0.44303352), np.float32(-0.46257916), np.float32(-0.52277595), np.float32(-0.50028944), np.float32(-0.5594064), np.float32(-0.42554745), np.float32(-0.43165272), np.float32(-0.49765787), np.float32(-0.4590839), np.float32(-0.51956576), np.float32(-0.4452071), np.float32(-0.43306908), np.float32(-0.4986575), np.float32(-0.42399925), np.float32(-0.5183483), np.float32(-0.5418989), np.float32(-0.54387313), np.float32(-0.41721138), np.float32(-0.5027693), np.float32(-0.50631696), np.float32(-0.5093173), np.float32(-0.3821223), np.float32(-0.4637021), np.float32(-0.44346252), np.float32(-0.52291477), np.float32(-0.5620501), np.float32(-0.55358887), np.float32(-0.48309964), np.float32(-0.32760236), np.float32(-0.57253706), np.float32(-0.5717862), np.float32(-0.5657669), np.float32(-0.49317795), np.float32(-0.5244601), np.float32(-0.544916), np.float32(-0.5373737), np.float32(-0.56530374), np.float32(-0.44027734), np.float32(-0.48818517), np.float32(-0.566051), np.float32(-0.6162163), np.float32(-0.45978385), np.float32(-0.47115567), np.float32(-0.44392464), np.float32(-0.5962756), np.float32(-0.5525789), np.float32(-0.5332187), np.float32(-0.5693787), np.float32(-0.5575467), np.float32(-0.46964335), np.float32(-0.5128202), np.float32(-0.53805345), np.float32(-0.48748544), np.float32(-0.3792828), np.float32(-0.52583545), np.float32(-0.4357098), np.float32(-0.46287668), np.float32(-0.5607835), np.float32(-0.5687721), np.float32(-0.5376203), np.float32(-0.5400239), np.float32(-0.5449283), np.float32(-0.51622903), np.float32(-0.45223755), np.float32(-0.5456331), np.float32(-0.5487034), np.float32(-0.43057808), np.float32(-0.3716735), np.float32(-0.55640674), np.float32(-0.5403391), np.float32(-0.33054656), np.float32(-0.47454056)]",
     "all_val_losses_tr_mode": "[]",
     "also_val_in_tr_mode": "False",
-    "amp_grad_scaler": "None",
+    "amp_grad_scaler": "<torch.cuda.amp.grad_scaler.GradScaler object at 0x7efb50930ad0>",
     "base_num_features": "30",
     "basic_generator_patch_size": "[205 205 205]",
     "batch_dice": "False",
     "batch_size": "2",
-    "best_MA_tr_loss_for_patience": "None",
-    "best_epoch_based_on_MA_tr_loss": "None",
-    "best_val_eval_criterion_MA": "None",
+    "best_MA_tr_loss_for_patience": "-0.6829764",
+    "best_epoch_based_on_MA_tr_loss": "140",
+    "best_val_eval_criterion_MA": "0.3936047",
     "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 0x7efe777c1fd0>",
-    "dl_val": "<nnunet_mednext.training.dataloading.dataset_loading.DataLoader3D object at 0x7efe778811d0>",
+    "dl_tr": "<nnunet_mednext.training.dataloading.dataset_loading.DataLoader3D object at 0x7efb50b09fd0>",
+    "dl_val": "<nnunet_mednext.training.dataloading.dataset_loading.DataLoader3D object at 0x7efb509411d0>",
     "do_dummy_2D_aug": "False",
     "ds_loss_weights": "[0.51612903 0.25806452 0.12903226 0.06451613 0.03225806 0.        ]",
-    "epoch": "0",
+    "epoch": "150",
     "experiment_name": "nnUNetTrainerV2_MedNeXt_L_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_L_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_L_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/training_log_2026_11_7_14_01_19.txt",
+    "log_file": "/marimo/TopBrain2026/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_L_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0/training_log_2026_11_8_06_34_55.txt",
     "lr_scheduler": "None",
     "lr_scheduler_eps": "0.001",
     "lr_scheduler_patience": "30",
@@ -53,7 +53,7 @@
     "online_eval_fp": "[]",
     "online_eval_tp": "[]",
     "only_keep_largest_connected_component": "None",
-    "optimizer": "AdamW (\nParameter Group 0\n    amsgrad: False\n    betas: (0.9, 0.999)\n    capturable: False\n    decoupled_weight_decay: True\n    differentiable: False\n    eps: 0.0001\n    foreach: None\n    fused: None\n    lr: 0.001\n    maximize: False\n    weight_decay: 3e-05\n)",
+    "optimizer": "AdamW (\nParameter Group 0\n    amsgrad: False\n    betas: (0.9, 0.999)\n    capturable: False\n    decoupled_weight_decay: True\n    differentiable: False\n    eps: 0.0001\n    foreach: None\n    fused: None\n    lr: 0.0008639269723028191\n    maximize: False\n    weight_decay: 3e-05\n)",
     "output_folder": "/marimo/TopBrain2026/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_L_kernel3__nnUNetPlansv2.1_trgSp_1x1x1/fold_0",
     "output_folder_base": "/marimo/TopBrain2026/nnUNet_results/nnUNet/3d_fullres/Task001_Brain2026/nnUNetTrainerV2_MedNeXt_L_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 0x7efe777c3620>",
+    "tr_gen": "<batchgenerators.dataloading.multi_threaded_augmenter.MultiThreadedAugmenter object at 0x7efb50b0b620>",
     "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 0x7efe77881f90>",
+    "val_gen": "<batchgenerators.dataloading.multi_threaded_augmenter.MultiThreadedAugmenter object at 0x7efb50941f90>",
     "was_initialized": "True",
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