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: 1.2388
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 |
|---|---|---|---|
| 2.0959 | 1.0 | 291 | 1.6893 |
| 1.6328 | 2.0 | 582 | 1.5211 |
| 1.4921 | 3.0 | 873 | 1.3554 |
| 1.4011 | 4.0 | 1164 | 1.3424 |
| 1.3351 | 5.0 | 1455 | 1.2614 |
| 1.2718 | 6.0 | 1746 | 1.3491 |
| 1.2216 | 7.0 | 2037 | 1.2867 |
| 1.206 | 8.0 | 2328 | 1.3365 |
| 1.1781 | 9.0 | 2619 | 1.2072 |
| 1.1338 | 10.0 | 2910 | 1.1643 |
| 1.1288 | 11.0 | 3201 | 1.1396 |
| 1.1012 | 12.0 | 3492 | 1.1911 |
| 1.0915 | 13.0 | 3783 | 1.2163 |
| 1.0746 | 14.0 | 4074 | 1.2091 |
| 1.0731 | 15.0 | 4365 | 1.2164 |
| 1.0491 | 16.0 | 4656 | 1.2388 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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