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HBERTv1_48_L12_H64_A2_massive
This model is a fine-tuned version of gokuls/HBERTv1_48_L12_H64_A2 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 1.8009
- Accuracy: 0.5553
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 |
|---|---|---|---|---|
| 3.9467 | 1.0 | 180 | 3.7242 | 0.1121 |
| 3.5338 | 2.0 | 360 | 3.3402 | 0.1121 |
| 3.2555 | 3.0 | 540 | 3.1034 | 0.1820 |
| 3.0004 | 4.0 | 720 | 2.8411 | 0.3074 |
| 2.7522 | 5.0 | 900 | 2.6134 | 0.3384 |
| 2.5415 | 6.0 | 1080 | 2.4233 | 0.3856 |
| 2.366 | 7.0 | 1260 | 2.2615 | 0.4112 |
| 2.2167 | 8.0 | 1440 | 2.1359 | 0.4609 |
| 2.1008 | 9.0 | 1620 | 2.0361 | 0.4835 |
| 2.0016 | 10.0 | 1800 | 1.9606 | 0.5061 |
| 1.9204 | 11.0 | 1980 | 1.8984 | 0.5298 |
| 1.8517 | 12.0 | 2160 | 1.8549 | 0.5352 |
| 1.8078 | 13.0 | 2340 | 1.8158 | 0.5499 |
| 1.78 | 14.0 | 2520 | 1.8009 | 0.5553 |
| 1.7531 | 15.0 | 2700 | 1.7919 | 0.5548 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0
