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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: 1.1665
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 |
|---|---|---|---|
| 2.1115 | 1.0 | 291 | 1.6910 |
| 1.6344 | 2.0 | 582 | 1.3645 |
| 1.4807 | 3.0 | 873 | 1.4238 |
| 1.3931 | 4.0 | 1164 | 1.4296 |
| 1.3413 | 5.0 | 1455 | 1.2654 |
| 1.2873 | 6.0 | 1746 | 1.3083 |
| 1.2302 | 7.0 | 2037 | 1.2093 |
| 1.2123 | 8.0 | 2328 | 1.2651 |
| 1.179 | 9.0 | 2619 | 1.2634 |
| 1.148 | 10.0 | 2910 | 1.2130 |
| 1.127 | 11.0 | 3201 | 1.2644 |
| 1.0993 | 12.0 | 3492 | 1.1545 |
| 1.0964 | 13.0 | 3783 | 1.1527 |
| 1.079 | 14.0 | 4074 | 1.0715 |
| 1.0662 | 15.0 | 4365 | 1.2462 |
| 1.067 | 16.0 | 4656 | 1.1665 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
