readme: ---
  tags: autotrain
  datasets:
  - abhishek/autotrain-data-vision_652fee16113a4f07a2452e021a22a934
  - sasha/dog-food
  co2_eq_emissions: 2.050948967287266
  model-index:
  - name: autotrain-dog-vs-food
    results:
    - task:
        name: Image Classification
        type: image-classification
      dataset:
        name: sasha/dog-food
        type: sasha/dog-food
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9976190476190476
    - task:
        type: image-classification
        name: Image Classification
      dataset:
        name: sasha/dog-food
        type: sasha/dog-food
        config: sasha--dog-food
        split: test
      metrics:
      - name: Accuracy
        type: accuracy
        value: 1.0
        verified: true
      - name: Precision
        type: precision
        value: 1.0
        verified: true
      - name: Recall
        type: recall
        value: 1.0
        verified: true
      - name: AUC
        type: auc
        value: 1.0
        verified: true
      - name: F1
        type: f1
        value: 1.0
        verified: true
      - name: loss
        type: loss
        value: 0.001115015591494739
        verified: true
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Multi-class Classification
  - Model ID: 264300
  - CO2 Emissions (in grams): 2.050948967287266
  
  ## Validation Metrics
  
  - Loss: 0.009216072037816048
  - Accuracy: 0.9976190476190476
  - Macro F1: 0.9973261861865685
  - Micro F1: 0.9976190476190476
  - Weighted F1: 0.997621154535828
  - Macro Precision: 0.9964539007092199
  - Micro Precision: 0.9976190476190476
  - Weighted Precision: 0.9976359338061465
  - Macro Recall: 0.9982142857142857
  - Micro Recall: 0.9976190476190476
  - Weighted Recall: 0.9976190476190476