bert_uncased_L-10_H-512_A-8_massive
This model is a fine-tuned version of google/bert_uncased_L-10_H-512_A-8 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.6000
- Accuracy: 0.8869
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 |
|---|---|---|---|---|
| 2.4668 | 1.0 | 180 | 1.3269 | 0.7511 |
| 1.0706 | 2.0 | 360 | 0.7806 | 0.8411 |
| 0.6117 | 3.0 | 540 | 0.6024 | 0.8662 |
| 0.3953 | 4.0 | 720 | 0.5695 | 0.8692 |
| 0.2706 | 5.0 | 900 | 0.5476 | 0.8751 |
| 0.1872 | 6.0 | 1080 | 0.5291 | 0.8775 |
| 0.1345 | 7.0 | 1260 | 0.5455 | 0.8770 |
| 0.0982 | 8.0 | 1440 | 0.5429 | 0.8844 |
| 0.067 | 9.0 | 1620 | 0.5639 | 0.8854 |
| 0.0513 | 10.0 | 1800 | 0.5952 | 0.8775 |
| 0.0392 | 11.0 | 1980 | 0.5867 | 0.8834 |
| 0.0305 | 12.0 | 2160 | 0.6004 | 0.8785 |
| 0.0241 | 13.0 | 2340 | 0.5916 | 0.8849 |
| 0.0202 | 14.0 | 2520 | 0.6000 | 0.8869 |
| 0.0187 | 15.0 | 2700 | 0.6025 | 0.8859 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1