metadata

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
            verified: true
          - name: Precision Macro
            type: precision
            value: 1
            verified: true
          - name: Precision Micro
            type: precision
            value: 1
            verified: true
          - name: Precision Weighted
            type: precision
            value: 1
            verified: true
          - name: Recall Macro
            type: recall
            value: 1
            verified: true
          - name: Recall Micro
            type: recall
            value: 1
            verified: true
          - name: Recall Weighted
            type: recall
            value: 1
            verified: true
          - name: F1 Macro
            type: f1
            value: 1
            verified: true
          - name: F1 Micro
            type: f1
            value: 1
            verified: true
          - name: F1 Weighted
            type: f1
            value: 1
            verified: true
          - name: loss
            type: loss
            value: 0.00001848173087637406
            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