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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: 1.2463
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 |
|---|---|---|---|
| 2.0991 | 1.0 | 291 | 1.6924 |
| 1.6398 | 2.0 | 582 | 1.4293 |
| 1.4878 | 3.0 | 873 | 1.3899 |
| 1.3995 | 4.0 | 1164 | 1.3814 |
| 1.3413 | 5.0 | 1455 | 1.1986 |
| 1.2802 | 6.0 | 1746 | 1.2751 |
| 1.2394 | 7.0 | 2037 | 1.2610 |
| 1.1993 | 8.0 | 2328 | 1.2118 |
| 1.1655 | 9.0 | 2619 | 1.1882 |
| 1.1406 | 10.0 | 2910 | 1.2225 |
| 1.129 | 11.0 | 3201 | 1.2082 |
| 1.104 | 12.0 | 3492 | 1.1654 |
| 1.0825 | 13.0 | 3783 | 1.2517 |
| 1.0739 | 14.0 | 4074 | 1.1687 |
| 1.0627 | 15.0 | 4365 | 1.1212 |
| 1.0623 | 16.0 | 4656 | 1.2463 |
Framework versions
- Transformers 4.16.2
- Pytorch 2.0.1+cu118
- Datasets 1.16.1
- Tokenizers 0.14.1
