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