bert_uncased_L-4_H-512_A-8_massive
This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.5260
- Accuracy: 0.8844
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 |
|---|---|---|---|---|
| 2.7044 | 1.0 | 180 | 1.5553 | 0.6901 |
| 1.2648 | 2.0 | 360 | 0.9088 | 0.8082 |
| 0.7783 | 3.0 | 540 | 0.6655 | 0.8539 |
| 0.5308 | 4.0 | 720 | 0.5876 | 0.8578 |
| 0.3865 | 5.0 | 900 | 0.5480 | 0.8716 |
| 0.2889 | 6.0 | 1080 | 0.5289 | 0.8746 |
| 0.2207 | 7.0 | 1260 | 0.5367 | 0.8756 |
| 0.1701 | 8.0 | 1440 | 0.5260 | 0.8844 |
| 0.1389 | 9.0 | 1620 | 0.5364 | 0.8819 |
| 0.1076 | 10.0 | 1800 | 0.5423 | 0.8834 |
| 0.0898 | 11.0 | 1980 | 0.5524 | 0.8795 |
| 0.0763 | 12.0 | 2160 | 0.5524 | 0.8829 |
| 0.0633 | 13.0 | 2340 | 0.5643 | 0.8805 |
| 0.0573 | 14.0 | 2520 | 0.5642 | 0.8819 |
| 0.0519 | 15.0 | 2700 | 0.5634 | 0.8805 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1