| | --- |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: DNADebertaSentencepiece30k_continuation_continuation_continuation |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # DNADebertaSentencepiece30k_continuation_continuation_continuation |
| | |
| | This model is a fine-tuned version of [Vlasta/DNADebertaSentencepiece30k_continuation_continuation](https://huggingface.co/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 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.19.2 |
| | - Pytorch 1.11.0 |
| | - Datasets 2.2.2 |
| | - Tokenizers 0.12.1 |
| |
|
