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mlm_gh_issues
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: 1.2449
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 |
|---|---|---|---|
| 2.099 | 1.0 | 291 | 1.6946 |
| 1.6396 | 2.0 | 582 | 1.4288 |
| 1.4875 | 3.0 | 873 | 1.3893 |
| 1.399 | 4.0 | 1164 | 1.3812 |
| 1.341 | 5.0 | 1455 | 1.2004 |
| 1.2803 | 6.0 | 1746 | 1.2738 |
| 1.2397 | 7.0 | 2037 | 1.2645 |
| 1.199 | 8.0 | 2328 | 1.2092 |
| 1.166 | 9.0 | 2619 | 1.1871 |
| 1.1406 | 10.0 | 2910 | 1.2244 |
| 1.1293 | 11.0 | 3201 | 1.2061 |
| 1.1037 | 12.0 | 3492 | 1.1621 |
| 1.0824 | 13.0 | 3783 | 1.2540 |
| 1.0738 | 14.0 | 4074 | 1.1703 |
| 1.0625 | 15.0 | 4365 | 1.1195 |
| 1.0628 | 16.0 | 4656 | 1.2449 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
