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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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## Model description
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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| No log | 1.0 | 204 |
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| No log | 2.0 | 408 |
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| 0.111 | 16.0 | 3264 | 1.8347 | 0.6722 |
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| 0.111 | 17.0 | 3468 | 1.8072 | 0.6780 |
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| 0.0988 | 18.0 | 3672 | 1.8371 | 0.6770 |
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| 0.0988 | 19.0 | 3876 | 1.8562 | 0.6741 |
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| 0.0907 | 20.0 | 4080 | 1.8583 | 0.6741 |
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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: 0.9064
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- Accuracy: 0.6591
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## Model description
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 15
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 204 | 0.9670 | 0.6052 |
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| No log | 2.0 | 408 | 0.8899 | 0.6731 |
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| 0.8476 | 3.0 | 612 | 0.9283 | 0.6722 |
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| 0.8476 | 4.0 | 816 | 1.0110 | 0.6828 |
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| 0.3419 | 5.0 | 1020 | 1.0947 | 0.6741 |
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| 0.3419 | 6.0 | 1224 | 1.1896 | 0.6799 |
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| 0.3419 | 7.0 | 1428 | 1.3467 | 0.6887 |
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| 0.193 | 8.0 | 1632 | 1.3716 | 0.6838 |
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| 0.193 | 9.0 | 1836 | 1.4742 | 0.6809 |
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| 0.1485 | 10.0 | 2040 | 1.5121 | 0.6867 |
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| 0.1485 | 11.0 | 2244 | 1.5670 | 0.6819 |
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| 0.1485 | 12.0 | 2448 | 1.5593 | 0.6867 |
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| 0.1185 | 13.0 | 2652 | 1.6455 | 0.6809 |
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| 0.1185 | 14.0 | 2856 | 1.6417 | 0.6877 |
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| 0.1077 | 15.0 | 3060 | 1.6399 | 0.6867 |
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### Framework versions
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