<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
HBERTv1_48_L4_H128_A2_massive
This model is a fine-tuned version of gokuls/HBERTv1_48_L4_H128_A2 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.9771
- Accuracy: 0.7585
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 |
|---|---|---|---|---|
| 3.7047 | 1.0 | 180 | 3.1694 | 0.2671 |
| 2.853 | 2.0 | 360 | 2.4727 | 0.3728 |
| 2.2985 | 3.0 | 540 | 2.0198 | 0.5037 |
| 1.8951 | 4.0 | 720 | 1.6943 | 0.5903 |
| 1.6002 | 5.0 | 900 | 1.4773 | 0.6385 |
| 1.3858 | 6.0 | 1080 | 1.3326 | 0.6606 |
| 1.2238 | 7.0 | 1260 | 1.2261 | 0.7044 |
| 1.1074 | 8.0 | 1440 | 1.1328 | 0.7270 |
| 1.0097 | 9.0 | 1620 | 1.0892 | 0.7364 |
| 0.9282 | 10.0 | 1800 | 1.0557 | 0.7408 |
| 0.8735 | 11.0 | 1980 | 1.0236 | 0.7457 |
| 0.8285 | 12.0 | 2160 | 1.0049 | 0.7555 |
| 0.7842 | 13.0 | 2340 | 0.9897 | 0.7550 |
| 0.7669 | 14.0 | 2520 | 0.9835 | 0.7555 |
| 0.7482 | 15.0 | 2700 | 0.9771 | 0.7585 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0
