bert_uncased_L-6_H-128_A-2_massive
This model is a fine-tuned version of google/bert_uncased_L-6_H-128_A-2 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 1.5439
- Accuracy: 0.7314
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 |
|---|---|---|---|---|
| 3.8348 | 1.0 | 180 | 3.5466 | 0.3192 |
| 3.3738 | 2.0 | 360 | 3.1057 | 0.4407 |
| 2.9882 | 3.0 | 540 | 2.7502 | 0.5140 |
| 2.6778 | 4.0 | 720 | 2.4684 | 0.5789 |
| 2.4276 | 5.0 | 900 | 2.2516 | 0.6158 |
| 2.2242 | 6.0 | 1080 | 2.0764 | 0.6419 |
| 2.0619 | 7.0 | 1260 | 1.9388 | 0.6827 |
| 1.932 | 8.0 | 1440 | 1.8294 | 0.6827 |
| 1.8283 | 9.0 | 1620 | 1.7395 | 0.6975 |
| 1.7411 | 10.0 | 1800 | 1.6747 | 0.7118 |
| 1.6698 | 11.0 | 1980 | 1.6142 | 0.7137 |
| 1.6176 | 12.0 | 2160 | 1.5737 | 0.7231 |
| 1.5796 | 13.0 | 2340 | 1.5439 | 0.7314 |
| 1.5509 | 14.0 | 2520 | 1.5284 | 0.7300 |
| 1.5409 | 15.0 | 2700 | 1.5226 | 0.7285 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1