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README.md
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This model is a fine-tuned version of [HueyNemud/das22-10-camembert_pretrained](https://huggingface.co/HueyNemud/das22-10-camembert_pretrained) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Ebegin: {'precision': 0.
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- Eend: {'precision': 0.
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- Overall Precision: 0.
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- Overall Recall: 0.
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- Overall F1: 0.
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- Overall Accuracy: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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| No log | 0.07 | 300 | 0.
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| 0.0585 | 0.93 | 3900 | 0.0259 | 0.9864 | 0.9899 | 0.9881 | 0.9922 |
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| 0.0478 | 1.0 | 4200 | 0.0314 | 0.9933 | 0.9649 | 0.9789 | 0.9862 |
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| 0.0842 | 1.07 | 4500 | 0.0222 | 0.9887 | 0.9897 | 0.9892 | 0.9928 |
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| 0.0842 | 1.14 | 4800 | 0.0189 | 0.9925 | 0.9883 | 0.9904 | 0.9937 |
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| 0.075 | 1.22 | 5100 | 0.0241 | 0.9890 | 0.9898 | 0.9894 | 0.9930 |
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| 0.075 | 1.29 | 5400 | 0.0242 | 0.9915 | 0.9854 | 0.9884 | 0.9924 |
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| 0.0511 | 1.36 | 5700 | 0.0197 | 0.9929 | 0.9885 | 0.9907 | 0.9939 |
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| 0.042 | 1.43 | 6000 | 0.0223 | 0.9936 | 0.9852 | 0.9894 | 0.9930 |
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| 0.042 | 1.5 | 6300 | 0.0203 | 0.9899 | 0.9905 | 0.9902 | 0.9935 |
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| 0.0596 | 1.57 | 6600 | 0.0215 | 0.9892 | 0.9914 | 0.9903 | 0.9936 |
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| 0.0596 | 1.65 | 6900 | 0.0211 | 0.9922 | 0.9875 | 0.9898 | 0.9933 |
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| 0.0489 | 1.72 | 7200 | 0.0212 | 0.9923 | 0.9869 | 0.9896 | 0.9931 |
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### Framework versions
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This model is a fine-tuned version of [HueyNemud/das22-10-camembert_pretrained](https://huggingface.co/HueyNemud/das22-10-camembert_pretrained) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0474
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- Ebegin: {'precision': 0.9822681935722202, 'recall': 0.9870081662954714, 'f1': 0.9846324754675061, 'number': 2694}
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- Eend: {'precision': 0.9790132547864506, 'recall': 0.9840858623242043, 'f1': 0.9815430047988187, 'number': 2702}
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- Overall Precision: 0.9806
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- Overall Recall: 0.9855
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- Overall F1: 0.9831
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- Overall Accuracy: 0.9880
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| No log | 0.07 | 300 | 0.0916 | 0.9560 | 0.9910 | 0.9731 | 0.9821 |
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| 0.32 | 0.14 | 600 | 0.0893 | 0.9919 | 0.9482 | 0.9695 | 0.9803 |
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| 0.32 | 0.21 | 900 | 0.0772 | 0.9903 | 0.9419 | 0.9655 | 0.9778 |
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| 0.114 | 0.29 | 1200 | 0.0442 | 0.9811 | 0.9798 | 0.9805 | 0.9871 |
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| 0.0983 | 0.36 | 1500 | 0.0351 | 0.9907 | 0.9826 | 0.9866 | 0.9912 |
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| 0.0983 | 0.43 | 1800 | 0.0325 | 0.9917 | 0.9856 | 0.9887 | 0.9926 |
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| 0.0869 | 0.5 | 2100 | 0.0237 | 0.9905 | 0.9938 | 0.9921 | 0.9948 |
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| 0.0869 | 0.57 | 2400 | 0.0316 | 0.9890 | 0.9870 | 0.9880 | 0.9921 |
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| 0.0844 | 0.64 | 2700 | 0.0271 | 0.9863 | 0.9892 | 0.9877 | 0.9919 |
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| 0.0794 | 0.72 | 3000 | 0.0287 | 0.9872 | 0.9901 | 0.9887 | 0.9926 |
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| 0.0794 | 0.79 | 3300 | 0.0281 | 0.9862 | 0.9891 | 0.9876 | 0.9918 |
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| 0.0561 | 0.86 | 3600 | 0.0259 | 0.9883 | 0.9934 | 0.9908 | 0.9939 |
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### Framework versions
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