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HBERTv1_48_L2_H128_A2_massive
This model is a fine-tuned version of gokuls/HBERTv1_48_L2_H128_A2 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 1.0382
- Accuracy: 0.7413
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 |
|---|---|---|---|---|
| 3.7441 | 1.0 | 180 | 3.2836 | 0.2022 |
| 2.9759 | 2.0 | 360 | 2.5939 | 0.3586 |
| 2.3963 | 3.0 | 540 | 2.0958 | 0.4786 |
| 1.9807 | 4.0 | 720 | 1.7821 | 0.5711 |
| 1.6992 | 5.0 | 900 | 1.5545 | 0.6104 |
| 1.4956 | 6.0 | 1080 | 1.4044 | 0.6399 |
| 1.3435 | 7.0 | 1260 | 1.2924 | 0.6778 |
| 1.2315 | 8.0 | 1440 | 1.2195 | 0.6945 |
| 1.1387 | 9.0 | 1620 | 1.1671 | 0.7088 |
| 1.0708 | 10.0 | 1800 | 1.1236 | 0.7186 |
| 1.0222 | 11.0 | 1980 | 1.0898 | 0.7265 |
| 0.9834 | 12.0 | 2160 | 1.0719 | 0.7314 |
| 0.9504 | 13.0 | 2340 | 1.0573 | 0.7388 |
| 0.9317 | 14.0 | 2520 | 1.0442 | 0.7378 |
| 0.9184 | 15.0 | 2700 | 1.0382 | 0.7413 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0
