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bert_uncased_L-6_H-256_A-4_massive
This model is a fine-tuned version of google/bert_uncased_L-6_H-256_A-4 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.6810
- Accuracy: 0.8559
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 |
|---|---|---|---|---|
| 3.414 | 1.0 | 180 | 2.7276 | 0.4629 |
| 2.4079 | 2.0 | 360 | 1.9650 | 0.6390 |
| 1.8021 | 3.0 | 540 | 1.5333 | 0.7221 |
| 1.4214 | 4.0 | 720 | 1.2586 | 0.7634 |
| 1.1564 | 5.0 | 900 | 1.0714 | 0.7900 |
| 0.966 | 6.0 | 1080 | 0.9539 | 0.8023 |
| 0.8253 | 7.0 | 1260 | 0.8706 | 0.8165 |
| 0.7209 | 8.0 | 1440 | 0.8109 | 0.8303 |
| 0.6401 | 9.0 | 1620 | 0.7647 | 0.8377 |
| 0.5755 | 10.0 | 1800 | 0.7404 | 0.8411 |
| 0.5227 | 11.0 | 1980 | 0.7118 | 0.8431 |
| 0.4854 | 12.0 | 2160 | 0.6995 | 0.8515 |
| 0.4528 | 13.0 | 2340 | 0.6902 | 0.8544 |
| 0.4399 | 14.0 | 2520 | 0.6810 | 0.8559 |
| 0.4285 | 15.0 | 2700 | 0.6820 | 0.8515 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1
