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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: 1.1415
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 |
|---|---|---|---|
| 1.6963 | 1.0 | 291 | 1.5992 |
| 1.5292 | 2.0 | 582 | 1.4419 |
| 1.4256 | 3.0 | 873 | 1.4078 |
| 1.3472 | 4.0 | 1164 | 1.2984 |
| 1.3002 | 5.0 | 1455 | 1.2909 |
| 1.2514 | 6.0 | 1746 | 1.3003 |
| 1.2022 | 7.0 | 2037 | 1.2514 |
| 1.1681 | 8.0 | 2328 | 1.2121 |
| 1.1532 | 9.0 | 2619 | 1.2843 |
| 1.1214 | 10.0 | 2910 | 1.2365 |
| 1.1247 | 11.0 | 3201 | 1.1365 |
| 1.1033 | 12.0 | 3492 | 1.2102 |
| 1.0748 | 13.0 | 3783 | 1.2221 |
| 1.0698 | 14.0 | 4074 | 1.1152 |
| 1.0534 | 15.0 | 4365 | 1.1890 |
| 1.065 | 16.0 | 4656 | 1.1415 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2
