Russian-BERT-Finetune
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README.md
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This model is a fine-tuned version of [Priyanka-Balivada/bert-3-epoch-sentiment](https://huggingface.co/Priyanka-Balivada/bert-3-epoch-sentiment) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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- Accuracy: 0.
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- Precision: 0.
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- Recall: 0.
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- Micro-avg-recall: 0.
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- Micro-avg-precision: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Micro-avg-recall | Micro-avg-precision |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:----------------:|:-------------------:|
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### Framework versions
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This model is a fine-tuned version of [Priyanka-Balivada/bert-3-epoch-sentiment](https://huggingface.co/Priyanka-Balivada/bert-3-epoch-sentiment) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0910
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- Accuracy: 0.869
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- Precision: 0.8687
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- Recall: 0.869
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- Micro-avg-recall: 0.869
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- Micro-avg-precision: 0.869
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Micro-avg-recall | Micro-avg-precision |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:----------------:|:-------------------:|
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| 0.1014 | 1.0 | 750 | 0.8994 | 0.845 | 0.8457 | 0.845 | 0.845 | 0.845 |
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| 0.1351 | 2.0 | 1500 | 1.0207 | 0.858 | 0.8629 | 0.858 | 0.858 | 0.858 |
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| 0.0001 | 3.0 | 2250 | 1.1304 | 0.8563 | 0.8566 | 0.8563 | 0.8563 | 0.8563 |
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| 0.0733 | 4.0 | 3000 | 1.0855 | 0.862 | 0.8624 | 0.862 | 0.862 | 0.862 |
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| 0.0005 | 5.0 | 3750 | 1.0910 | 0.869 | 0.8687 | 0.869 | 0.869 | 0.869 |
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### Framework versions
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model.safetensors
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