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: 1.2540
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 |
|---|---|---|---|
| 2.0981 | 1.0 | 291 | 1.6917 |
| 1.6493 | 2.0 | 582 | 1.4357 |
| 1.4831 | 3.0 | 873 | 1.3923 |
| 1.3957 | 4.0 | 1164 | 1.4056 |
| 1.3339 | 5.0 | 1455 | 1.1944 |
| 1.2936 | 6.0 | 1746 | 1.2888 |
| 1.2458 | 7.0 | 2037 | 1.2715 |
| 1.2004 | 8.0 | 2328 | 1.1992 |
| 1.1785 | 9.0 | 2619 | 1.1726 |
| 1.1389 | 10.0 | 2910 | 1.2157 |
| 1.1313 | 11.0 | 3201 | 1.1977 |
| 1.0935 | 12.0 | 3492 | 1.1794 |
| 1.0826 | 13.0 | 3783 | 1.2260 |
| 1.0729 | 14.0 | 4074 | 1.1549 |
| 1.0599 | 15.0 | 4365 | 1.1269 |
| 1.0538 | 16.0 | 4656 | 1.2540 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.2
- Datasets 1.16.1
- Tokenizers 0.10.3
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