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bert_uncased_L-8_H-128_A-2_massive
This model is a fine-tuned version of google/bert_uncased_L-8_H-128_A-2 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 1.4687
- Accuracy: 0.7334
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 |
|---|---|---|---|---|
| 3.7982 | 1.0 | 180 | 3.4791 | 0.3335 |
| 3.287 | 2.0 | 360 | 3.0244 | 0.4299 |
| 2.8916 | 3.0 | 540 | 2.6675 | 0.5047 |
| 2.5836 | 4.0 | 720 | 2.3965 | 0.5839 |
| 2.3397 | 5.0 | 900 | 2.1824 | 0.6291 |
| 2.1423 | 6.0 | 1080 | 2.0132 | 0.6680 |
| 1.9823 | 7.0 | 1260 | 1.8773 | 0.6872 |
| 1.8543 | 8.0 | 1440 | 1.7682 | 0.6940 |
| 1.7528 | 9.0 | 1620 | 1.6818 | 0.7049 |
| 1.6612 | 10.0 | 1800 | 1.6191 | 0.7118 |
| 1.595 | 11.0 | 1980 | 1.5608 | 0.7226 |
| 1.5406 | 12.0 | 2160 | 1.5231 | 0.7270 |
| 1.4997 | 13.0 | 2340 | 1.4922 | 0.7309 |
| 1.4719 | 14.0 | 2520 | 1.4760 | 0.7329 |
| 1.4595 | 15.0 | 2700 | 1.4687 | 0.7334 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1
