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HBERTv1_48_L4_H512_A8_massive
This model is a fine-tuned version of gokuls/HBERTv1_48_L4_H512_A8 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.7982
- Accuracy: 0.8628
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 |
|---|---|---|---|---|
| 2.2635 | 1.0 | 180 | 1.0540 | 0.7378 |
| 0.852 | 2.0 | 360 | 0.7276 | 0.8067 |
| 0.5577 | 3.0 | 540 | 0.6679 | 0.8224 |
| 0.3964 | 4.0 | 720 | 0.6441 | 0.8352 |
| 0.28 | 5.0 | 900 | 0.6340 | 0.8441 |
| 0.2055 | 6.0 | 1080 | 0.6703 | 0.8470 |
| 0.1508 | 7.0 | 1260 | 0.6997 | 0.8465 |
| 0.1185 | 8.0 | 1440 | 0.7411 | 0.8480 |
| 0.0889 | 9.0 | 1620 | 0.7219 | 0.8519 |
| 0.0652 | 10.0 | 1800 | 0.7566 | 0.8613 |
| 0.0477 | 11.0 | 1980 | 0.7694 | 0.8564 |
| 0.0331 | 12.0 | 2160 | 0.7993 | 0.8578 |
| 0.0247 | 13.0 | 2340 | 0.7982 | 0.8628 |
| 0.0174 | 14.0 | 2520 | 0.8348 | 0.8554 |
| 0.0141 | 15.0 | 2700 | 0.8415 | 0.8583 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0
