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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: 1.2500
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 |
|---|---|---|---|
| 2.0975 | 1.0 | 291 | 1.7060 |
| 1.648 | 2.0 | 582 | 1.4280 |
| 1.4837 | 3.0 | 873 | 1.3980 |
| 1.3978 | 4.0 | 1164 | 1.4040 |
| 1.3314 | 5.0 | 1455 | 1.2032 |
| 1.2954 | 6.0 | 1746 | 1.2814 |
| 1.2448 | 7.0 | 2037 | 1.2635 |
| 1.1983 | 8.0 | 2328 | 1.2071 |
| 1.1849 | 9.0 | 2619 | 1.1675 |
| 1.1414 | 10.0 | 2910 | 1.2095 |
| 1.1314 | 11.0 | 3201 | 1.1858 |
| 1.0943 | 12.0 | 3492 | 1.1658 |
| 1.0838 | 13.0 | 3783 | 1.2336 |
| 1.0733 | 14.0 | 4074 | 1.1606 |
| 1.0627 | 15.0 | 4365 | 1.1188 |
| 1.055 | 16.0 | 4656 | 1.2500 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3
