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DNADebertaSentencepiece30k_continuation_continuation

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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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+
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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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+
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+ # DNADebertaSentencepiece30k_continuation_continuation
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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