readme: ---
  tags: autotrain
  datasets:
  - abhishek/autotrain-data-vision_79ca848474e24ad3a520c09e36452e85
  - cifar10
  co2_eq_emissions: 32.869648157119876
  model-index:
  - name: autotrain_cifar10_vit_base
    results:
    - task:
        name: Image Classification
        type: image-classification
      dataset:
        name: cifar10
        type: cifar10
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9834
    - task:
        type: image-classification
        name: Image Classification
      dataset:
        name: cifar10
        type: cifar10
        config: plain_text
        split: test
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9811
        verified: true
      - name: Precision Macro
        type: precision
        value: 0.9812371727477451
        verified: true
      - name: Precision Micro
        type: precision
        value: 0.9811
        verified: true
      - name: Precision Weighted
        type: precision
        value: 0.9812371727477451
        verified: true
      - name: Recall Macro
        type: recall
        value: 0.9811
        verified: true
      - name: Recall Micro
        type: recall
        value: 0.9811
        verified: true
      - name: Recall Weighted
        type: recall
        value: 0.9811
        verified: true
      - name: F1 Macro
        type: f1
        value: 0.9811240087824231
        verified: true
      - name: F1 Micro
        type: f1
        value: 0.9811
        verified: true
      - name: F1 Weighted
        type: f1
        value: 0.981124008782423
        verified: true
      - name: loss
        type: loss
        value: 0.0649944543838501
        verified: true
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Multi-class Classification
  - Model ID: 300303
  - CO2 Emissions (in grams): 32.869648157119876
  
  ## Validation Metrics
  
  - Loss: 0.05070499703288078
  - Accuracy: 0.9834
  - Macro F1: 0.9834026834840477
  - Micro F1: 0.9834
  - Weighted F1: 0.9834026834840479
  - Macro Precision: 0.9834502145172822
  - Micro Precision: 0.9834
  - Weighted Precision: 0.9834502145172822
  - Macro Recall: 0.9833999999999999
  - Micro Recall: 0.9834
  - Weighted Recall: 0.9834