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NimaBoscarino
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dog_food

Image Classification
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PyTorch
Trained with AutoTrain
vision
Eval Results
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dog_food / README.md
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metadata
library_name: transformers
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
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:
          - type: accuracy
            value: 1
            name: Accuracy
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            value: 1
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          - type: precision
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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