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HBERTv1_48_L6_H64_A2_massive
This model is a fine-tuned version of gokuls/HBERTv1_48_L6_H64_A2 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 2.0289
- Accuracy: 0.4540
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 |
|---|---|---|---|---|
| 3.9723 | 1.0 | 180 | 3.7638 | 0.0910 |
| 3.5915 | 2.0 | 360 | 3.4160 | 0.1402 |
| 3.3315 | 3.0 | 540 | 3.1858 | 0.1545 |
| 3.0936 | 4.0 | 720 | 2.9377 | 0.2489 |
| 2.8827 | 5.0 | 900 | 2.7454 | 0.2607 |
| 2.7034 | 6.0 | 1080 | 2.5719 | 0.3005 |
| 2.5548 | 7.0 | 1260 | 2.4456 | 0.3301 |
| 2.4205 | 8.0 | 1440 | 2.3437 | 0.3689 |
| 2.3213 | 9.0 | 1620 | 2.2482 | 0.4043 |
| 2.2359 | 10.0 | 1800 | 2.1809 | 0.4112 |
| 2.1724 | 11.0 | 1980 | 2.1286 | 0.4289 |
| 2.1113 | 12.0 | 2160 | 2.0921 | 0.4442 |
| 2.067 | 13.0 | 2340 | 2.0534 | 0.4471 |
| 2.0388 | 14.0 | 2520 | 2.0381 | 0.4501 |
| 2.0222 | 15.0 | 2700 | 2.0289 | 0.4540 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0
