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DNADebertaSentencepiece30k

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deberta
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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: DNADebertaSentencepiece10k
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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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+ # DNADebertaSentencepiece10k
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+
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+ This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 5.5666
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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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+ | 7.1504 | 0.36 | 5000 | 7.0604 |
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+ | 7.0431 | 0.72 | 10000 | 7.0307 |
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+ | 7.0219 | 1.08 | 15000 | 7.0186 |
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+ | 7.0099 | 1.45 | 20000 | 7.0058 |
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+ | 6.9686 | 1.81 | 25000 | 6.8723 |
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+ | 6.8449 | 2.17 | 30000 | 6.7980 |
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+ | 6.7654 | 2.53 | 35000 | 6.7057 |
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+ | 6.6418 | 2.89 | 40000 | 6.5286 |
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+ | 6.4225 | 3.25 | 45000 | 6.2286 |
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+ | 6.1859 | 3.61 | 50000 | 6.0729 |
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+ | 6.0727 | 3.97 | 55000 | 5.9866 |
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+ | 5.998 | 4.34 | 60000 | 5.9212 |
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+ | 5.945 | 4.7 | 65000 | 5.8824 |
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+ | 5.904 | 5.06 | 70000 | 5.8446 |
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+ | 5.8689 | 5.42 | 75000 | 5.8139 |
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+ | 5.8431 | 5.78 | 80000 | 5.7862 |
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+ | 5.8186 | 6.14 | 85000 | 5.7655 |
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+ | 5.7957 | 6.5 | 90000 | 5.7447 |
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+ | 5.7803 | 6.86 | 95000 | 5.7249 |
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+ | 5.765 | 7.23 | 100000 | 5.7107 |
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+ | 5.747 | 7.59 | 105000 | 5.7004 |
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+ | 5.7345 | 7.95 | 110000 | 5.6835 |
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+ | 5.7221 | 8.31 | 115000 | 5.6728 |
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+ | 5.7106 | 8.67 | 120000 | 5.6622 |
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+ | 5.7018 | 9.03 | 125000 | 5.6516 |
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+ | 5.692 | 9.39 | 130000 | 5.6390 |
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+ | 5.6791 | 9.75 | 135000 | 5.6313 |
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+ | 5.6751 | 10.12 | 140000 | 5.6250 |
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+ | 5.6649 | 10.48 | 145000 | 5.6182 |
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+ | 5.6601 | 10.84 | 150000 | 5.6103 |
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+ | 5.6542 | 11.2 | 155000 | 5.6059 |
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+ | 5.6468 | 11.56 | 160000 | 5.5957 |
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+ | 5.6393 | 11.92 | 165000 | 5.5915 |
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+ | 5.6362 | 12.28 | 170000 | 5.5880 |
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+ | 5.6328 | 12.64 | 175000 | 5.5835 |
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+ | 5.6261 | 13.01 | 180000 | 5.5775 |
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+ | 5.6218 | 13.37 | 185000 | 5.5753 |
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+ | 5.6215 | 13.73 | 190000 | 5.5701 |
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+ | 5.6163 | 14.09 | 195000 | 5.5697 |
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+ | 5.6151 | 14.45 | 200000 | 5.5667 |
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+ | 5.6129 | 14.81 | 205000 | 5.5651 |
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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