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: 1.2314
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: 64
- eval_batch_size: 16
- 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 |
|---|---|---|---|
| 2.193 | 1.0 | 146 | 1.7004 |
| 1.7081 | 2.0 | 292 | 1.4895 |
| 1.5458 | 3.0 | 438 | 1.4427 |
| 1.4715 | 4.0 | 584 | 1.4081 |
| 1.3944 | 5.0 | 730 | 1.3163 |
| 1.3396 | 6.0 | 876 | 1.3200 |
| 1.2945 | 7.0 | 1022 | 1.2785 |
| 1.2652 | 8.0 | 1168 | 1.2473 |
| 1.2332 | 9.0 | 1314 | 1.2321 |
| 1.2042 | 10.0 | 1460 | 1.2162 |
| 1.204 | 11.0 | 1606 | 1.1781 |
| 1.1866 | 12.0 | 1752 | 1.2211 |
| 1.1592 | 13.0 | 1898 | 1.2801 |
| 1.1503 | 14.0 | 2044 | 1.1768 |
| 1.1268 | 15.0 | 2190 | 1.1657 |
| 1.1521 | 16.0 | 2336 | 1.2314 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0
- Datasets 2.2.3.dev0
- Tokenizers 0.12.1
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