DNADebertaSentencepiece10k_continuation_continuation_continuation
This model is a fine-tuned version of Vlasta/DNADebertaSentencepiece10k_continuation_continuation on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.2605
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 |
|---|---|---|---|
| 5.4076 | 0.36 | 5000 | 5.3702 |
| 5.4146 | 0.72 | 10000 | 5.3677 |
| 5.4119 | 1.08 | 15000 | 5.3661 |
| 5.4093 | 1.45 | 20000 | 5.3577 |
| 5.4055 | 1.81 | 25000 | 5.3574 |
| 5.3987 | 2.17 | 30000 | 5.3539 |
| 5.3974 | 2.53 | 35000 | 5.3509 |
| 5.3931 | 2.89 | 40000 | 5.3431 |
| 5.387 | 3.25 | 45000 | 5.3447 |
| 5.3868 | 3.61 | 50000 | 5.3404 |
| 5.3874 | 3.97 | 55000 | 5.3362 |
| 5.3797 | 4.34 | 60000 | 5.3275 |
| 5.3775 | 4.7 | 65000 | 5.3316 |
| 5.3737 | 5.06 | 70000 | 5.3245 |
| 5.367 | 5.42 | 75000 | 5.3228 |
| 5.3679 | 5.78 | 80000 | 5.3193 |
| 5.3648 | 6.14 | 85000 | 5.3185 |
| 5.3586 | 6.5 | 90000 | 5.3149 |
| 5.361 | 6.86 | 95000 | 5.3086 |
| 5.3572 | 7.23 | 100000 | 5.3080 |
| 5.3521 | 7.59 | 105000 | 5.3057 |
| 5.3516 | 7.95 | 110000 | 5.3020 |
| 5.3481 | 8.31 | 115000 | 5.2997 |
| 5.3453 | 8.67 | 120000 | 5.2990 |
| 5.3446 | 9.03 | 125000 | 5.2951 |
| 5.3418 | 9.39 | 130000 | 5.2888 |
| 5.3341 | 9.75 | 135000 | 5.2860 |
| 5.3371 | 10.12 | 140000 | 5.2879 |
| 5.3319 | 10.48 | 145000 | 5.2845 |
| 5.3316 | 10.84 | 150000 | 5.2822 |
| 5.3306 | 11.2 | 155000 | 5.2803 |
| 5.3272 | 11.56 | 160000 | 5.2743 |
| 5.3224 | 11.92 | 165000 | 5.2724 |
| 5.3224 | 12.28 | 170000 | 5.2726 |
| 5.3217 | 12.64 | 175000 | 5.2712 |
| 5.3167 | 13.01 | 180000 | 5.2663 |
| 5.3148 | 13.37 | 185000 | 5.2659 |
| 5.3154 | 13.73 | 190000 | 5.2624 |
| 5.3119 | 14.09 | 195000 | 5.2627 |
| 5.3122 | 14.45 | 200000 | 5.2599 |
| 5.3091 | 14.81 | 205000 | 5.2586 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0
- Datasets 2.2.2
- Tokenizers 0.12.1