Commit From AutoTrain

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.tar.gz filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+tags:
+- autotrain
+- vision
+- image-classification
+datasets:
+- Kaludi/autotrain-data-updated-food-category-classification
+widget:
+- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
+  example_title: Tiger
+- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
+  example_title: Teapot
+- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg
+  example_title: Palace
+co2_eq_emissions:
+  emissions: 12.456278925446485
+---
+
+# Model Trained Using AutoTrain
+
+- Problem type: Multi-class Classification
+- Model ID: 3353292434
+- CO2 Emissions (in grams): 12.4563
+
+## Validation Metrics
+
+- Loss: 0.144
+- Accuracy: 0.960
+- Macro F1: 0.959
+- Micro F1: 0.960
+- Weighted F1: 0.959
+- Macro Precision: 0.962
+- Micro Precision: 0.960
+- Weighted Precision: 0.962
+- Macro Recall: 0.960
+- Micro Recall: 0.960
+- Weighted Recall: 0.960

config.json

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+{
+  "_name_or_path": "AutoTrain",
+  "architectures": [
+    "SwinForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "depths": [
+    2,
+    2,
+    18,
+    2
+  ],
+  "drop_path_rate": 0.1,
+  "embed_dim": 128,
+  "encoder_stride": 32,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "Bread",
+    "1": "Dairy",
+    "10": "Soup",
+    "11": "Vegetable",
+    "2": "Dessert",
+    "3": "Egg",
+    "4": "Fried Food",
+    "5": "Fruit",
+    "6": "Meat",
+    "7": "Noodles",
+    "8": "Rice",
+    "9": "Seafood"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "Bread": "0",
+    "Dairy": "1",
+    "Dessert": "2",
+    "Egg": "3",
+    "Fried Food": "4",
+    "Fruit": "5",
+    "Meat": "6",
+    "Noodles": "7",
+    "Rice": "8",
+    "Seafood": "9",
+    "Soup": "10",
+    "Vegetable": "11"
+  },
+  "layer_norm_eps": 1e-05,
+  "max_length": 128,
+  "mlp_ratio": 4.0,
+  "model_type": "swin",
+  "num_channels": 3,
+  "num_heads": [
+    4,
+    8,
+    16,
+    32
+  ],
+  "num_layers": 4,
+  "padding": "max_length",
+  "patch_size": 4,
+  "path_norm": true,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.25.1",
+  "use_absolute_embeddings": false,
+  "window_size": 7
+}

preprocessor_config.json

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+{
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "feature_extractor_type": "ViTFeatureExtractor",
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ViTImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

pytorch_model.bin

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+size 347640721