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bert-base-uncased-issues-128
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2109
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.9845 | 1.0 | 1163 | 1.6403 |
| 1.5695 | 2.0 | 2326 | 1.4212 |
| 1.4221 | 3.0 | 3489 | 1.3714 |
| 1.3302 | 4.0 | 4652 | 1.3592 |
| 1.2734 | 5.0 | 5815 | 1.2781 |
| 1.2143 | 6.0 | 6978 | 1.2286 |
| 1.1704 | 7.0 | 8141 | 1.2492 |
| 1.1261 | 8.0 | 9304 | 1.2044 |
| 1.0812 | 9.0 | 10467 | 1.1878 |
| 1.0657 | 10.0 | 11630 | 1.2177 |
| 1.0319 | 11.0 | 12793 | 1.1428 |
| 1.0063 | 12.0 | 13956 | 1.0910 |
| 0.9731 | 13.0 | 15119 | 1.1111 |
| 0.9674 | 14.0 | 16282 | 1.1699 |
| 0.9391 | 15.0 | 17445 | 1.0805 |
| 0.9381 | 16.0 | 18608 | 1.2109 |
Framework versions
- Transformers 4.8.0
- Pytorch 1.9.0+cu111
- Datasets 1.18.3
- Tokenizers 0.10.3
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