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HBERTv1_48_L12_H128_A2_massive
This model is a fine-tuned version of gokuls/HBERTv1_48_L12_H128_A2 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 1.0042
- Accuracy: 0.7732
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 |
|---|---|---|---|---|
| 3.7792 | 1.0 | 180 | 3.3305 | 0.1913 |
| 3.0177 | 2.0 | 360 | 2.6809 | 0.2371 |
| 2.451 | 3.0 | 540 | 2.1770 | 0.4260 |
| 2.0079 | 4.0 | 720 | 1.8072 | 0.5780 |
| 1.681 | 5.0 | 900 | 1.5486 | 0.6350 |
| 1.4431 | 6.0 | 1080 | 1.3891 | 0.6695 |
| 1.2574 | 7.0 | 1260 | 1.2684 | 0.7049 |
| 1.1169 | 8.0 | 1440 | 1.1950 | 0.7152 |
| 1.0107 | 9.0 | 1620 | 1.1286 | 0.7418 |
| 0.9139 | 10.0 | 1800 | 1.0791 | 0.7590 |
| 0.8467 | 11.0 | 1980 | 1.0527 | 0.7580 |
| 0.7838 | 12.0 | 2160 | 1.0343 | 0.7639 |
| 0.7331 | 13.0 | 2340 | 1.0309 | 0.7673 |
| 0.7004 | 14.0 | 2520 | 1.0077 | 0.7713 |
| 0.6797 | 15.0 | 2700 | 1.0042 | 0.7732 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0
