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bert-large-uncased-sst-2-16-13-30
This model is a fine-tuned version of bert-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6328
- Accuracy: 0.625
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: 1.5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 1 | 0.7326 | 0.5 |
| No log | 2.0 | 2 | 0.7299 | 0.5 |
| No log | 3.0 | 3 | 0.7258 | 0.5 |
| No log | 4.0 | 4 | 0.7173 | 0.5 |
| No log | 5.0 | 5 | 0.7098 | 0.5 |
| No log | 6.0 | 6 | 0.7019 | 0.4688 |
| No log | 7.0 | 7 | 0.6969 | 0.5 |
| No log | 8.0 | 8 | 0.6889 | 0.5312 |
| No log | 9.0 | 9 | 0.6846 | 0.5625 |
| 0.6763 | 10.0 | 10 | 0.6781 | 0.5625 |
| 0.6763 | 11.0 | 11 | 0.6697 | 0.5938 |
| 0.6763 | 12.0 | 12 | 0.6681 | 0.625 |
| 0.6763 | 13.0 | 13 | 0.6675 | 0.625 |
| 0.6763 | 14.0 | 14 | 0.6668 | 0.625 |
| 0.6763 | 15.0 | 15 | 0.6666 | 0.625 |
| 0.6763 | 16.0 | 16 | 0.6648 | 0.5938 |
| 0.6763 | 17.0 | 17 | 0.6607 | 0.625 |
| 0.6763 | 18.0 | 18 | 0.6589 | 0.6562 |
| 0.6763 | 19.0 | 19 | 0.6564 | 0.6562 |
| 0.4935 | 20.0 | 20 | 0.6533 | 0.6562 |
| 0.4935 | 21.0 | 21 | 0.6502 | 0.6562 |
| 0.4935 | 22.0 | 22 | 0.6472 | 0.5938 |
| 0.4935 | 23.0 | 23 | 0.6445 | 0.5938 |
| 0.4935 | 24.0 | 24 | 0.6418 | 0.5938 |
| 0.4935 | 25.0 | 25 | 0.6391 | 0.5938 |
| 0.4935 | 26.0 | 26 | 0.6370 | 0.5938 |
| 0.4935 | 27.0 | 27 | 0.6353 | 0.5938 |
| 0.4935 | 28.0 | 28 | 0.6341 | 0.625 |
| 0.4935 | 29.0 | 29 | 0.6333 | 0.625 |
| 0.3659 | 30.0 | 30 | 0.6328 | 0.625 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.4.0
- Tokenizers 0.13.3
