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README.md
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@@ -33,15 +33,18 @@ This model is a fine-tuned version of [microsoft/dit-base](https://huggingface.c
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It achieves the following results on the evaluation set:
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- Loss: 0.0786
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- Accuracy: 0.9767
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## Model description
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
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| 0.1535 | 1.0 | 208 | 0.1126 | 0.9622 | 0.9597 | 0.9622 | 0.5711 | 0.9622 | 0.9622 | 0.5925 | 0.9577 | 0.9622 | 0.5531 |
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| 0.1195 | 2.0 | 416 | 0.0843 | 0.9738 | 0.9736 | 0.9738 | 0.8502 | 0.9738 | 0.9738 | 0.8037 | 0.9741 | 0.9738 | 0.9287 |
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| 0.0979 | 3.0 | 624 | 0.0786 | 0.9767 | 0.9768 | 0.9767 | 0.9154 | 0.9767 | 0.9767 | 0.9019 | 0.9771 | 0.9767 | 0.9314 |
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### Framework versions
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- Transformers 4.28.1
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It achieves the following results on the evaluation set:
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- Loss: 0.0786
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- Accuracy: 0.9767
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- F1
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- Weighted: 0.9768
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- Micro: 0.9767
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- Macro: 0.9154
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- Recall
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- Weighted: 0.9767
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- Micro: 0.9767
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- Macro: 0.9019
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- Precision
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- Weighted: 0.9771
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- Micro: 0.9767
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- Macro: 0.9314
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## Model description
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted F1 | Micro F1 | Macro F1 | Weighted Recall | Micro Recall | Macro Recall | Weighted Precision | Micro Precision | Macro Precision |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
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| 0.1535 | 1.0 | 208 | 0.1126 | 0.9622 | 0.9597 | 0.9622 | 0.5711 | 0.9622 | 0.9622 | 0.5925 | 0.9577 | 0.9622 | 0.5531 |
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| 0.1195 | 2.0 | 416 | 0.0843 | 0.9738 | 0.9736 | 0.9738 | 0.8502 | 0.9738 | 0.9738 | 0.8037 | 0.9741 | 0.9738 | 0.9287 |
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| 0.0979 | 3.0 | 624 | 0.0786 | 0.9767 | 0.9768 | 0.9767 | 0.9154 | 0.9767 | 0.9767 | 0.9019 | 0.9771 | 0.9767 | 0.9314 |
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### Framework versions
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- Transformers 4.28.1
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