bert_uncased_L-10_H-128_A-2_massive
This model is a fine-tuned version of google/bert_uncased_L-10_H-128_A-2 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 1.4064
- Accuracy: 0.7467
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 |
|---|---|---|---|---|
| 3.8032 | 1.0 | 180 | 3.4795 | 0.3296 |
| 3.2716 | 2.0 | 360 | 2.9915 | 0.4491 |
| 2.8593 | 3.0 | 540 | 2.6360 | 0.5145 |
| 2.5442 | 4.0 | 720 | 2.3533 | 0.5765 |
| 2.296 | 5.0 | 900 | 2.1403 | 0.6006 |
| 2.0936 | 6.0 | 1080 | 1.9655 | 0.6463 |
| 1.9277 | 7.0 | 1260 | 1.8291 | 0.6719 |
| 1.7937 | 8.0 | 1440 | 1.7114 | 0.6911 |
| 1.6829 | 9.0 | 1620 | 1.6267 | 0.7088 |
| 1.5946 | 10.0 | 1800 | 1.5575 | 0.7231 |
| 1.5258 | 11.0 | 1980 | 1.4976 | 0.7354 |
| 1.4663 | 12.0 | 2160 | 1.4616 | 0.7364 |
| 1.4256 | 13.0 | 2340 | 1.4296 | 0.7437 |
| 1.3984 | 14.0 | 2520 | 1.4126 | 0.7442 |
| 1.3824 | 15.0 | 2700 | 1.4064 | 0.7467 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1