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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: 1.3226
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: 128
- 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 |
|---|---|---|---|
| 2.3267 | 1.0 | 73 | 1.8862 |
| 1.774 | 2.0 | 146 | 1.5454 |
| 1.6001 | 3.0 | 219 | 1.4916 |
| 1.5111 | 4.0 | 292 | 1.4676 |
| 1.449 | 5.0 | 365 | 1.3100 |
| 1.3855 | 6.0 | 438 | 1.4255 |
| 1.3522 | 7.0 | 511 | 1.2901 |
| 1.3262 | 8.0 | 584 | 1.3294 |
| 1.292 | 9.0 | 657 | 1.3458 |
| 1.2746 | 10.0 | 730 | 1.3086 |
| 1.2515 | 11.0 | 803 | 1.2175 |
| 1.2399 | 12.0 | 876 | 1.1521 |
| 1.2226 | 13.0 | 949 | 1.2453 |
| 1.2148 | 14.0 | 1022 | 1.1466 |
| 1.2084 | 15.0 | 1095 | 1.3008 |
| 1.1964 | 16.0 | 1168 | 1.3226 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.0
- Tokenizers 0.13.3
