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: 1.2490
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: 32
- 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 |
|---|---|---|---|
| 2.0988 | 1.0 | 291 | 1.6923 |
| 1.6379 | 2.0 | 582 | 1.4303 |
| 1.4844 | 3.0 | 873 | 1.3849 |
| 1.3972 | 4.0 | 1164 | 1.3730 |
| 1.34 | 5.0 | 1455 | 1.1839 |
| 1.2827 | 6.0 | 1746 | 1.2908 |
| 1.2406 | 7.0 | 2037 | 1.2598 |
| 1.1985 | 8.0 | 2328 | 1.2100 |
| 1.1655 | 9.0 | 2619 | 1.1782 |
| 1.1416 | 10.0 | 2910 | 1.2136 |
| 1.128 | 11.0 | 3201 | 1.2038 |
| 1.1063 | 12.0 | 3492 | 1.1693 |
| 1.0799 | 13.0 | 3783 | 1.2501 |
| 1.0776 | 14.0 | 4074 | 1.1643 |
| 1.0635 | 15.0 | 4365 | 1.1193 |
| 1.061 | 16.0 | 4656 | 1.2490 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.11.0
- Tokenizers 0.13.2