Training in progress, epoch 1

.gitignore

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+checkpoint-*/

config.json

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+{
+  "_name_or_path": "microsoft/resnet-50",
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_first_stage": false,
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "AnnualCrop",
+    "1": "Forest",
+    "2": "HerbaceousVegetation",
+    "3": "Highway",
+    "4": "Industrial",
+    "5": "Pasture",
+    "6": "PermanentCrop",
+    "7": "Residential",
+    "8": "River",
+    "9": "SeaLake"
+  },
+  "label2id": {
+    "AnnualCrop": 0,
+    "Forest": 1,
+    "HerbaceousVegetation": 2,
+    "Highway": 3,
+    "Industrial": 4,
+    "Pasture": 5,
+    "PermanentCrop": 6,
+    "Residential": 7,
+    "River": 8,
+    "SeaLake": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.23.1"
+}

preprocessor_config.json

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+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_resize": true,
+  "feature_extractor_type": "ConvNextFeatureExtractor",
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "size": 224
+}

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