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README.md

@@ -1,3 +1,96 @@
 ---
-license: openrail
+tags:
+- autotrain
+- vision
+- image-classification
+datasets:
+- lewtun/dog_food
+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
+library_name: transformers
+co2_eq_emissions:
+  emissions: 6.799888815236616
+eval_info:
+  col_mapping: test
+model-index:
+- name: NimaBoscarino/dog_food
+  results:
+  - task:
+      type: image-classification
+      name: Image Classification
+    dataset:
+      name: lewtun/dog_food
+      type: lewtun/dog_food
+      config: lewtun--dog_food
+      split: test
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 1.0
+      verified: true
+    - name: Precision Macro
+      type: precision
+      value: 1.0
+      verified: true
+    - name: Precision Micro
+      type: precision
+      value: 1.0
+      verified: true
+    - name: Precision Weighted
+      type: precision
+      value: 1.0
+      verified: true
+    - name: Recall Macro
+      type: recall
+      value: 1.0
+      verified: true
+    - name: Recall Micro
+      type: recall
+      value: 1.0
+      verified: true
+    - name: Recall Weighted
+      type: recall
+      value: 1.0
+      verified: true
+    - name: F1 Macro
+      type: f1
+      value: 1.0
+      verified: true
+    - name: F1 Micro
+      type: f1
+      value: 1.0
+      verified: true
+    - name: F1 Weighted
+      type: f1
+      value: 1.0
+      verified: true
+    - name: loss
+      type: loss
+      value: 1.848173087637406e-05
+      verified: true
 ---
+
+# Model Trained Using AutoTrain
+
+- Problem type: Multi-class Classification
+- Model ID: 1647758504
+- CO2 Emissions (in grams): 6.7999
+
+## Validation Metrics
+
+- Loss: 0.001
+- Accuracy: 1.000
+- Macro F1: 1.000
+- Micro F1: 1.000
+- Weighted F1: 1.000
+- Macro Precision: 1.000
+- Micro Precision: 1.000
+- Weighted Precision: 1.000
+- Macro Recall: 1.000
+- Micro Recall: 1.000
+- Weighted Recall: 1.000

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": "chicken",
+    "1": "dog",
+    "2": "muffin"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "chicken": "0",
+    "dog": "1",
+    "muffin": "2"
+  },
+  "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": "4.22.1",
+  "use_absolute_embeddings": false,
+  "window_size": 7
+}

preprocessor_config.json

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

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c0781bb85cfa7a97b833282d84103641703fcbf681717807f946848b70839d04
+size 347600575