Training in progress, epoch 0

config.json

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+{
+  "_name_or_path": "facebook/convnextv2-large-1k-224",
+  "architectures": [
+    "ConvNextV2ForImageClassification"
+  ],
+  "depths": [
+    3,
+    3,
+    27,
+    3
+  ],
+  "drop_path_rate": 0.0,
+  "hidden_act": "gelu",
+  "hidden_sizes": [
+    192,
+    384,
+    768,
+    1536
+  ],
+  "id2label": {
+    "0": "Lung-Benign_Tissue",
+    "1": "Lung_Adenocarcinoma",
+    "2": "Lung_Squamous_Cell_Carcinoma"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "Lung-Benign_Tissue": 0,
+    "Lung_Adenocarcinoma": 1,
+    "Lung_Squamous_Cell_Carcinoma": 2
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "convnextv2",
+  "num_channels": 3,
+  "num_stages": 4,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "patch_size": 4,
+  "problem_type": "single_label_classification",
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.32.0"
+}

preprocessor_config.json

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+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}

pytorch_model.bin

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+oid sha256:cd7156c112b64da7653b4a845cb1ee5a09567fe16e0f62f11226dd00f0aaca64
+size 785830205

training_args.bin

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+oid sha256:9af2ed5889f2910df74de51ed40d8ad26fdb54641f1a4a8b797d4271707aa376
+size 4219