vision
Browse files
README.md
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- autotrain
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- image-classification
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- eligapris
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base_model: microsoft/resnet-152
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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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3. **Performance on Majority vs Minority Classes**: The higher micro and weighted scores compared to macro scores indicate that the model performs better on more frequent classes. This is likely due to the class imbalance, with the model potentially struggling more with the Gray_Leaf_Spot class.
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4. **Overall Performance**: With an accuracy of 85.85%, the model shows good overall performance. However, there's room for improvement, especially in handling the class imbalance.
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- autotrain
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- image-classification
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- eligapris
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- vision
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base_model: microsoft/resnet-152
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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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| 109 |
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3. **Performance on Majority vs Minority Classes**: The higher micro and weighted scores compared to macro scores indicate that the model performs better on more frequent classes. This is likely due to the class imbalance, with the model potentially struggling more with the Gray_Leaf_Spot class.
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4. **Overall Performance**: With an accuracy of 85.85%, the model shows good overall performance. However, there's room for improvement, especially in handling the class imbalance.
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