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DNADebertaSentencepiece30k_continuation_continuation_continuation
This model is a fine-tuned version of Vlasta/DNADebertaSentencepiece30k_continuation_continuation on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.9319
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 |
|---|---|---|---|
| 6.0844 | 0.41 | 5000 | 6.0623 |
| 6.0962 | 0.81 | 10000 | 6.0659 |
| 6.0903 | 1.22 | 15000 | 6.0566 |
| 6.0874 | 1.62 | 20000 | 6.0550 |
| 6.082 | 2.03 | 25000 | 6.0485 |
| 6.0756 | 2.44 | 30000 | 6.0446 |
| 6.0722 | 2.84 | 35000 | 6.0429 |
| 6.0698 | 3.25 | 40000 | 6.0317 |
| 6.0627 | 3.66 | 45000 | 6.0297 |
| 6.0606 | 4.06 | 50000 | 6.0301 |
| 6.0521 | 4.47 | 55000 | 6.0224 |
| 6.0526 | 4.87 | 60000 | 6.0159 |
| 6.0473 | 5.28 | 65000 | 6.0140 |
| 6.0435 | 5.69 | 70000 | 6.0076 |
| 6.039 | 6.09 | 75000 | 6.0022 |
| 6.032 | 6.5 | 80000 | 6.0037 |
| 6.0319 | 6.91 | 85000 | 5.9979 |
| 6.0232 | 7.31 | 90000 | 5.9937 |
| 6.0279 | 7.72 | 95000 | 5.9844 |
| 6.0198 | 8.12 | 100000 | 5.9854 |
| 6.0165 | 8.53 | 105000 | 5.9796 |
| 6.0153 | 8.94 | 110000 | 5.9741 |
| 6.0111 | 9.34 | 115000 | 5.9722 |
| 6.0082 | 9.75 | 120000 | 5.9679 |
| 6.0035 | 10.16 | 125000 | 5.9654 |
| 5.999 | 10.56 | 130000 | 5.9624 |
| 5.998 | 10.97 | 135000 | 5.9572 |
| 5.9926 | 11.37 | 140000 | 5.9535 |
| 5.9927 | 11.78 | 145000 | 5.9533 |
| 5.9903 | 12.19 | 150000 | 5.9517 |
| 5.986 | 12.59 | 155000 | 5.9459 |
| 5.9816 | 13.0 | 160000 | 5.9439 |
| 5.9786 | 13.41 | 165000 | 5.9390 |
| 5.9781 | 13.81 | 170000 | 5.9357 |
| 5.9779 | 14.22 | 175000 | 5.9346 |
| 5.9756 | 14.62 | 180000 | 5.9339 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0
- Datasets 2.2.2
- Tokenizers 0.12.1
