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HBERTv1_48_L4_H256_A4_massive
This model is a fine-tuned version of gokuls/HBERTv1_48_L4_H256_A4 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.7151
- Accuracy: 0.8401
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 |
|---|---|---|---|---|
| 3.206 | 1.0 | 180 | 2.2341 | 0.4579 |
| 1.8169 | 2.0 | 360 | 1.3642 | 0.6749 |
| 1.1697 | 3.0 | 540 | 1.0289 | 0.7423 |
| 0.8587 | 4.0 | 720 | 0.8583 | 0.7821 |
| 0.6723 | 5.0 | 900 | 0.8038 | 0.8008 |
| 0.5497 | 6.0 | 1080 | 0.7459 | 0.8101 |
| 0.4755 | 7.0 | 1260 | 0.7419 | 0.8146 |
| 0.3992 | 8.0 | 1440 | 0.7095 | 0.8278 |
| 0.336 | 9.0 | 1620 | 0.7278 | 0.8288 |
| 0.2956 | 10.0 | 1800 | 0.7151 | 0.8401 |
| 0.2593 | 11.0 | 1980 | 0.7130 | 0.8347 |
| 0.2301 | 12.0 | 2160 | 0.7215 | 0.8367 |
| 0.2038 | 13.0 | 2340 | 0.7191 | 0.8372 |
| 0.1881 | 14.0 | 2520 | 0.7273 | 0.8362 |
| 0.1766 | 15.0 | 2700 | 0.7256 | 0.8401 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0
