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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: DNADebertaSentencepiece30k_continuation_continuation |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# DNADebertaSentencepiece30k_continuation_continuation |
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This model is a fine-tuned version of [Vlasta/DNADebertaSentencepiece30k_continuation](https://huggingface.co/Vlasta/DNADebertaSentencepiece30k_continuation) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 5.9867 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 15 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:------:|:---------------:| |
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| 6.1786 | 0.41 | 5000 | 6.1475 | |
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| 6.1856 | 0.81 | 10000 | 6.1490 | |
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| 6.1769 | 1.22 | 15000 | 6.1370 | |
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| 6.1714 | 1.62 | 20000 | 6.1330 | |
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| 6.1633 | 2.03 | 25000 | 6.1221 | |
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| 6.1548 | 2.44 | 30000 | 6.1180 | |
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| 6.1495 | 2.84 | 35000 | 6.1141 | |
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| 6.1453 | 3.25 | 40000 | 6.1026 | |
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| 6.1362 | 3.66 | 45000 | 6.0984 | |
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| 6.1325 | 4.06 | 50000 | 6.0961 | |
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| 6.1227 | 4.47 | 55000 | 6.0874 | |
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| 6.1215 | 4.87 | 60000 | 6.0806 | |
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| 6.1149 | 5.28 | 65000 | 6.0779 | |
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| 6.1099 | 5.69 | 70000 | 6.0701 | |
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| 6.104 | 6.09 | 75000 | 6.0633 | |
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| 6.0963 | 6.5 | 80000 | 6.0628 | |
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| 6.095 | 6.91 | 85000 | 6.0572 | |
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| 6.0858 | 7.31 | 90000 | 6.0525 | |
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| 6.0895 | 7.72 | 95000 | 6.0430 | |
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| 6.0804 | 8.12 | 100000 | 6.0437 | |
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| 6.0767 | 8.53 | 105000 | 6.0371 | |
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| 6.0748 | 8.94 | 110000 | 6.0312 | |
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| 6.0702 | 9.34 | 115000 | 6.0293 | |
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| 6.0668 | 9.75 | 120000 | 6.0242 | |
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| 6.0615 | 10.16 | 125000 | 6.0213 | |
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| 6.0568 | 10.56 | 130000 | 6.0183 | |
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| 6.0552 | 10.97 | 135000 | 6.0125 | |
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| 6.0496 | 11.37 | 140000 | 6.0087 | |
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| 6.0493 | 11.78 | 145000 | 6.0084 | |
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| 6.0466 | 12.19 | 150000 | 6.0060 | |
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| 6.042 | 12.59 | 155000 | 6.0008 | |
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| 6.0375 | 13.0 | 160000 | 5.9986 | |
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| 6.0345 | 13.41 | 165000 | 5.9940 | |
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| 6.0336 | 13.81 | 170000 | 5.9905 | |
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| 6.0334 | 14.22 | 175000 | 5.9891 | |
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| 6.0313 | 14.62 | 180000 | 5.9887 | |
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### Framework versions |
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- Transformers 4.19.2 |
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- Pytorch 1.11.0 |
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- Datasets 2.2.2 |
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- Tokenizers 0.12.1 |
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