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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: 6.5337
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 |
|---|---|---|---|
| 2.1064 | 1.0 | 291 | 1.6942 |
| 1.6327 | 2.0 | 582 | 1.3707 |
| 1.4819 | 3.0 | 873 | 1.4033 |
| 1.3965 | 4.0 | 1164 | 1.4341 |
| 4.5167 | 5.0 | 1455 | 6.2129 |
| 6.1184 | 6.0 | 1746 | 6.2606 |
| 5.9894 | 7.0 | 2037 | 6.2949 |
| 5.9044 | 8.0 | 2328 | 6.3017 |
| 5.8635 | 9.0 | 2619 | 6.3110 |
| 5.8388 | 10.0 | 2910 | 6.4275 |
| 5.793 | 11.0 | 3201 | 6.3408 |
| 5.7428 | 12.0 | 3492 | 6.4123 |
| 5.7203 | 13.0 | 3783 | 6.4774 |
| 5.7021 | 14.0 | 4074 | 6.4178 |
| 5.6754 | 15.0 | 4365 | 6.5968 |
| 5.6586 | 16.0 | 4656 | 6.5337 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.3
