bert_uncased_L-8_H-256_A-4_massive
This model is a fine-tuned version of google/bert_uncased_L-8_H-256_A-4 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.6529
- Accuracy: 0.8618
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 |
|---|---|---|---|---|
| 3.4012 | 1.0 | 180 | 2.6862 | 0.5268 |
| 2.3339 | 2.0 | 360 | 1.8775 | 0.6793 |
| 1.7107 | 3.0 | 540 | 1.4277 | 0.7526 |
| 1.3323 | 4.0 | 720 | 1.1676 | 0.7964 |
| 1.0741 | 5.0 | 900 | 1.0010 | 0.8111 |
| 0.8903 | 6.0 | 1080 | 0.8893 | 0.8269 |
| 0.757 | 7.0 | 1260 | 0.8285 | 0.8342 |
| 0.6586 | 8.0 | 1440 | 0.7609 | 0.8455 |
| 0.5814 | 9.0 | 1620 | 0.7194 | 0.8480 |
| 0.5163 | 10.0 | 1800 | 0.6987 | 0.8519 |
| 0.4728 | 11.0 | 1980 | 0.6760 | 0.8549 |
| 0.4371 | 12.0 | 2160 | 0.6659 | 0.8608 |
| 0.4053 | 13.0 | 2340 | 0.6592 | 0.8613 |
| 0.3867 | 14.0 | 2520 | 0.6523 | 0.8608 |
| 0.3784 | 15.0 | 2700 | 0.6529 | 0.8618 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1