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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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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size:
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- eval_batch_size:
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.
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- Tokenizers 0.13.2
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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: 1.1947
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- Accuracy: 0.6793
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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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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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 20
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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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| 1.2761 | 1.0 | 102 | 1.3225 | 0.3375 |
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| 0.9847 | 2.0 | 204 | 1.0792 | 0.5509 |
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| 0.6882 | 3.0 | 306 | 0.9260 | 0.6382 |
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| 0.5099 | 4.0 | 408 | 0.9072 | 0.6634 |
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| 0.4614 | 5.0 | 510 | 0.9115 | 0.6867 |
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| 0.3406 | 6.0 | 612 | 1.0022 | 0.6751 |
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| 0.189 | 7.0 | 714 | 1.0881 | 0.6751 |
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| 0.2179 | 8.0 | 816 | 1.1520 | 0.6712 |
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| 0.2085 | 9.0 | 918 | 1.2567 | 0.6896 |
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| 0.1914 | 10.0 | 1020 | 1.2074 | 0.6828 |
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| 0.1271 | 11.0 | 1122 | 1.3389 | 0.6887 |
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| 0.1236 | 12.0 | 1224 | 1.3539 | 0.6790 |
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| 0.0946 | 13.0 | 1326 | 1.4042 | 0.6838 |
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| 0.0968 | 14.0 | 1428 | 1.4079 | 0.6877 |
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| 0.1095 | 15.0 | 1530 | 1.4884 | 0.6799 |
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| 0.1102 | 16.0 | 1632 | 1.5244 | 0.6790 |
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| 0.1159 | 17.0 | 1734 | 1.5238 | 0.6799 |
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| 0.1448 | 18.0 | 1836 | 1.5568 | 0.6780 |
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| 0.1105 | 19.0 | 1938 | 1.5629 | 0.6780 |
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| 0.092 | 20.0 | 2040 | 1.5588 | 0.6809 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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