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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: DNADebertaK6_Fruitfly |
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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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# DNADebertaK6_Fruitfly |
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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: 1.7137 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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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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- training_steps: 600001 |
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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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| 4.5584 | 5.36 | 20000 | 1.9795 | |
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| 1.9682 | 10.73 | 40000 | 1.8618 | |
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| 1.8692 | 16.09 | 60000 | 1.8273 | |
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| 1.8339 | 21.45 | 80000 | 1.8076 | |
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| 1.8208 | 26.82 | 100000 | 1.8073 | |
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| 1.8105 | 32.18 | 120000 | 1.7925 | |
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| 1.8022 | 37.54 | 140000 | 1.7909 | |
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| 1.7955 | 42.91 | 160000 | 1.7836 | |
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| 1.7907 | 48.27 | 180000 | 1.7769 | |
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| 1.7849 | 53.63 | 200000 | 1.7755 | |
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| 1.7805 | 59.0 | 220000 | 1.7677 | |
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| 1.7769 | 64.36 | 240000 | 1.7690 | |
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| 1.7723 | 69.72 | 260000 | 1.7614 | |
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| 1.7689 | 75.09 | 280000 | 1.7586 | |
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| 1.7646 | 80.45 | 300000 | 1.7523 | |
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| 1.7607 | 85.81 | 320000 | 1.7484 | |
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| 1.7572 | 91.18 | 340000 | 1.7458 | |
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| 1.754 | 96.54 | 360000 | 1.7460 | |
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| 1.7498 | 101.9 | 380000 | 1.7326 | |
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| 1.7463 | 107.27 | 400000 | 1.7377 | |
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| 1.7438 | 112.63 | 420000 | 1.7318 | |
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| 1.7406 | 117.99 | 440000 | 1.7342 | |
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| 1.7383 | 123.36 | 460000 | 1.7339 | |
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| 1.7348 | 128.72 | 480000 | 1.7244 | |
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| 1.7324 | 134.08 | 500000 | 1.7236 | |
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| 1.7289 | 139.45 | 520000 | 1.7155 | |
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| 1.7268 | 144.81 | 540000 | 1.7254 | |
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| 1.725 | 150.17 | 560000 | 1.7191 | |
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| 1.7221 | 155.54 | 580000 | 1.7147 | |
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| 1.7209 | 160.9 | 600000 | 1.7137 | |
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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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