bert_uncased_L-8_H-512_A-8_massive
This model is a fine-tuned version of google/bert_uncased_L-8_H-512_A-8 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.6061
- Accuracy: 0.8839
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: 64
- eval_batch_size: 64
- seed: 33
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.4813 | 1.0 | 180 | 1.3295 | 0.7506 |
| 1.0577 | 2.0 | 360 | 0.7897 | 0.8318 |
| 0.6168 | 3.0 | 540 | 0.6254 | 0.8623 |
| 0.404 | 4.0 | 720 | 0.5679 | 0.8672 |
| 0.2787 | 5.0 | 900 | 0.5594 | 0.8647 |
| 0.1993 | 6.0 | 1080 | 0.5499 | 0.8746 |
| 0.1406 | 7.0 | 1260 | 0.5674 | 0.8706 |
| 0.1044 | 8.0 | 1440 | 0.5678 | 0.8770 |
| 0.0775 | 9.0 | 1620 | 0.5668 | 0.8829 |
| 0.0565 | 10.0 | 1800 | 0.5830 | 0.8829 |
| 0.044 | 11.0 | 1980 | 0.6016 | 0.8785 |
| 0.0342 | 12.0 | 2160 | 0.6061 | 0.8839 |
| 0.0298 | 13.0 | 2340 | 0.6151 | 0.8815 |
| 0.0247 | 14.0 | 2520 | 0.6126 | 0.8810 |
| 0.0208 | 15.0 | 2700 | 0.6156 | 0.8829 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1