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autotrain_cifar10_vit_base

Image Classification
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vit
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autotrain_cifar10_vit_base / README.md
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Add evaluation results on cifar10 dataset (#2)
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metadata
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