DNADebertaSentencepiece30k_continuation_continuation
This model is a fine-tuned version of Vlasta/DNADebertaSentencepiece30k_continuation on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.9867
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 6.1786 | 0.41 | 5000 | 6.1475 |
| 6.1856 | 0.81 | 10000 | 6.1490 |
| 6.1769 | 1.22 | 15000 | 6.1370 |
| 6.1714 | 1.62 | 20000 | 6.1330 |
| 6.1633 | 2.03 | 25000 | 6.1221 |
| 6.1548 | 2.44 | 30000 | 6.1180 |
| 6.1495 | 2.84 | 35000 | 6.1141 |
| 6.1453 | 3.25 | 40000 | 6.1026 |
| 6.1362 | 3.66 | 45000 | 6.0984 |
| 6.1325 | 4.06 | 50000 | 6.0961 |
| 6.1227 | 4.47 | 55000 | 6.0874 |
| 6.1215 | 4.87 | 60000 | 6.0806 |
| 6.1149 | 5.28 | 65000 | 6.0779 |
| 6.1099 | 5.69 | 70000 | 6.0701 |
| 6.104 | 6.09 | 75000 | 6.0633 |
| 6.0963 | 6.5 | 80000 | 6.0628 |
| 6.095 | 6.91 | 85000 | 6.0572 |
| 6.0858 | 7.31 | 90000 | 6.0525 |
| 6.0895 | 7.72 | 95000 | 6.0430 |
| 6.0804 | 8.12 | 100000 | 6.0437 |
| 6.0767 | 8.53 | 105000 | 6.0371 |
| 6.0748 | 8.94 | 110000 | 6.0312 |
| 6.0702 | 9.34 | 115000 | 6.0293 |
| 6.0668 | 9.75 | 120000 | 6.0242 |
| 6.0615 | 10.16 | 125000 | 6.0213 |
| 6.0568 | 10.56 | 130000 | 6.0183 |
| 6.0552 | 10.97 | 135000 | 6.0125 |
| 6.0496 | 11.37 | 140000 | 6.0087 |
| 6.0493 | 11.78 | 145000 | 6.0084 |
| 6.0466 | 12.19 | 150000 | 6.0060 |
| 6.042 | 12.59 | 155000 | 6.0008 |
| 6.0375 | 13.0 | 160000 | 5.9986 |
| 6.0345 | 13.41 | 165000 | 5.9940 |
| 6.0336 | 13.81 | 170000 | 5.9905 |
| 6.0334 | 14.22 | 175000 | 5.9891 |
| 6.0313 | 14.62 | 180000 | 5.9887 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0
- Datasets 2.2.2
- Tokenizers 0.12.1