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--- |
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tags: |
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- autotrain |
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- vision |
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- image-classification |
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datasets: |
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- juliensimon/autotrain-data-food101 |
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widget: |
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg |
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example_title: Tiger |
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg |
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example_title: Teapot |
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg |
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example_title: Palace |
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co2_eq_emissions: |
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emissions: 179.11544810549532 |
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--- |
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# Usage |
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``` |
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from transformers import pipeline |
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p = pipeline("image-classification", model="juliensimon/autotrain-food101-1471154053") |
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result = p("my_image.jpg") |
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``` |
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# Model Trained Using AutoTrain |
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- Problem type: Multi-class Classification |
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- Model ID: 1471154053 |
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- CO2 Emissions (in grams): 179.1154 |
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## Validation Metrics |
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- Loss: 0.301 |
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- Accuracy: 0.915 |
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- Macro F1: 0.915 |
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- Micro F1: 0.915 |
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- Weighted F1: 0.915 |
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- Macro Precision: 0.917 |
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- Micro Precision: 0.915 |
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- Weighted Precision: 0.917 |
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- Macro Recall: 0.915 |
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- Micro Recall: 0.915 |
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- Weighted Recall: 0.915 |
