bert-large
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: 0.9621
- Accuracy: 0.8887
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: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 782 | 0.2848 | 0.8852 |
| 0.3133 | 2.0 | 1564 | 0.3038 | 0.8888 |
| 0.1751 | 3.0 | 2346 | 0.5035 | 0.8791 |
| 0.1057 | 4.0 | 3128 | 0.5942 | 0.885 |
| 0.1057 | 5.0 | 3910 | 0.5220 | 0.8764 |
| 0.0733 | 6.0 | 4692 | 0.6981 | 0.8823 |
| 0.0439 | 7.0 | 5474 | 0.6775 | 0.8833 |
| 0.0371 | 8.0 | 6256 | 0.6118 | 0.8891 |
| 0.0277 | 9.0 | 7038 | 0.7128 | 0.8864 |
| 0.0277 | 10.0 | 7820 | 0.7555 | 0.8868 |
| 0.0202 | 11.0 | 8602 | 0.7618 | 0.8888 |
| 0.0141 | 12.0 | 9384 | 0.7654 | 0.8842 |
| 0.0125 | 13.0 | 10166 | 0.8345 | 0.8867 |
| 0.0125 | 14.0 | 10948 | 0.8073 | 0.8844 |
| 0.0077 | 15.0 | 11730 | 0.7047 | 0.8887 |
| 0.0071 | 16.0 | 12512 | 0.8622 | 0.8891 |
| 0.004 | 17.0 | 13294 | 0.8655 | 0.8900 |
| 0.0031 | 18.0 | 14076 | 0.9096 | 0.8898 |
| 0.0031 | 19.0 | 14858 | 0.9454 | 0.8892 |
| 0.0016 | 20.0 | 15640 | 0.9621 | 0.8887 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2