Priyanka-Balivada
commited on
bert-russian
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- model.safetensors +1 -1
README.md
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) 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 [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0126
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- Accuracy: 0.8813
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- Precision: 0.8813
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- Recall: 0.8813
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- Micro-avg-recall: 0.8813
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- Micro-avg-precision: 0.8813
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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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| 0.0795 | 1.0 | 750 | 0.8896 | 0.8637 | 0.8665 | 0.8637 | 0.8637 | 0.8637 |
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| 0.073 | 2.0 | 1500 | 0.8294 | 0.8633 | 0.8640 | 0.8633 | 0.8633 | 0.8633 |
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| 0.0001 | 3.0 | 2250 | 0.9873 | 0.8757 | 0.8779 | 0.8757 | 0.8757 | 0.8757 |
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| 0.0432 | 4.0 | 3000 | 0.9801 | 0.8813 | 0.8817 | 0.8813 | 0.8813 | 0.8813 |
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| 0.0002 | 5.0 | 3750 | 1.0126 | 0.8813 | 0.8813 | 0.8813 | 0.8813 | 0.8813 |
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### Framework versions
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model.safetensors
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