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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: 1.2529
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 |
|---|---|---|---|
| 2.1006 | 1.0 | 291 | 1.7028 |
| 1.653 | 2.0 | 582 | 1.4206 |
| 1.486 | 3.0 | 873 | 1.3993 |
| 1.396 | 4.0 | 1164 | 1.3890 |
| 1.3329 | 5.0 | 1455 | 1.1999 |
| 1.2962 | 6.0 | 1746 | 1.2835 |
| 1.2454 | 7.0 | 2037 | 1.2793 |
| 1.2014 | 8.0 | 2328 | 1.2005 |
| 1.183 | 9.0 | 2619 | 1.1730 |
| 1.1396 | 10.0 | 2910 | 1.2259 |
| 1.1327 | 11.0 | 3201 | 1.1999 |
| 1.0988 | 12.0 | 3492 | 1.1731 |
| 1.0813 | 13.0 | 3783 | 1.2428 |
| 1.0744 | 14.0 | 4074 | 1.1532 |
| 1.0608 | 15.0 | 4365 | 1.1236 |
| 1.0532 | 16.0 | 4656 | 1.2529 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.9.0+cu111
- Datasets 2.10.1
- Tokenizers 0.13.2
