Training in progress, epoch 0

.gitignore

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+checkpoint-*/

config.json

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+{
+  "_name_or_path": "facebook/convnext-tiny-224",
+  "architectures": [
+    "ConvNextForImageClassification"
+  ],
+  "depths": [
+    3,
+    3,
+    9,
+    3
+  ],
+  "drop_path_rate": 0.0,
+  "hidden_act": "gelu",
+  "hidden_sizes": [
+    96,
+    192,
+    384,
+    768
+  ],
+  "id2label": {
+    "0": "Audemars Piguet",
+    "1": "Breguet",
+    "2": "Breitling",
+    "3": "Maurice Lacroix",
+    "4": "Omega",
+    "5": "Patek Philippe",
+    "6": "Rado",
+    "7": "Rolex",
+    "8": "Tissot",
+    "9": "Vacheron Constantin"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "Audemars Piguet": 0,
+    "Breguet": 1,
+    "Breitling": 2,
+    "Maurice Lacroix": 3,
+    "Omega": 4,
+    "Patek Philippe": 5,
+    "Rado": 6,
+    "Rolex": 7,
+    "Tissot": 8,
+    "Vacheron Constantin": 9
+  },
+  "layer_norm_eps": 1e-12,
+  "layer_scale_init_value": 1e-06,
+  "model_type": "convnext",
+  "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": "4.30.0"
+}

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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runs/Apr15_09-23-58_2fcc55d47541/events.out.tfevents.1713173730.2fcc55d47541.23030.0

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training_args.bin

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