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: 1.2620
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 |
|---|---|---|---|
| 2.0973 | 1.0 | 291 | 1.7221 |
| 1.6473 | 2.0 | 582 | 1.4317 |
| 1.4839 | 3.0 | 873 | 1.3902 |
| 1.3942 | 4.0 | 1164 | 1.3860 |
| 1.3345 | 5.0 | 1455 | 1.1929 |
| 1.2933 | 6.0 | 1746 | 1.2842 |
| 1.2457 | 7.0 | 2037 | 1.2714 |
| 1.2002 | 8.0 | 2328 | 1.1975 |
| 1.1833 | 9.0 | 2619 | 1.1701 |
| 1.1412 | 10.0 | 2910 | 1.2135 |
| 1.1316 | 11.0 | 3201 | 1.1978 |
| 1.0989 | 12.0 | 3492 | 1.1710 |
| 1.0832 | 13.0 | 3783 | 1.2304 |
| 1.0727 | 14.0 | 4074 | 1.1565 |
| 1.0591 | 15.0 | 4365 | 1.1271 |
| 1.0535 | 16.0 | 4656 | 1.2620 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.10.0
- Datasets 2.7.1
- Tokenizers 0.12.1
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