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HBERTv1_48_L6_H128_A2_massive
This model is a fine-tuned version of gokuls/HBERTv1_48_L6_H128_A2 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.9439
- Accuracy: 0.7791
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 |
|---|---|---|---|---|
| 3.7427 | 1.0 | 180 | 3.3038 | 0.2110 |
| 3.0115 | 2.0 | 360 | 2.6361 | 0.3601 |
| 2.4129 | 3.0 | 540 | 2.1001 | 0.4988 |
| 1.946 | 4.0 | 720 | 1.7411 | 0.5617 |
| 1.6252 | 5.0 | 900 | 1.4891 | 0.6188 |
| 1.3825 | 6.0 | 1080 | 1.3293 | 0.6508 |
| 1.201 | 7.0 | 1260 | 1.2183 | 0.6990 |
| 1.074 | 8.0 | 1440 | 1.1335 | 0.7304 |
| 0.9698 | 9.0 | 1620 | 1.0699 | 0.7472 |
| 0.8878 | 10.0 | 1800 | 1.0251 | 0.7555 |
| 0.8286 | 11.0 | 1980 | 0.9941 | 0.7629 |
| 0.7817 | 12.0 | 2160 | 0.9766 | 0.7678 |
| 0.7388 | 13.0 | 2340 | 0.9558 | 0.7703 |
| 0.7157 | 14.0 | 2520 | 0.9489 | 0.7782 |
| 0.6877 | 15.0 | 2700 | 0.9439 | 0.7791 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0
