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tags: |
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- generated_from_trainer |
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model-index: |
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- name: DNADebertaK6_Arabidopsis |
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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_Arabidopsis |
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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: 1.7194 |
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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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| 4.6174 | 6.12 | 20000 | 1.9257 | |
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| 1.8873 | 12.24 | 40000 | 1.8098 | |
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| 1.8213 | 18.36 | 60000 | 1.7952 | |
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| 1.8042 | 24.48 | 80000 | 1.7888 | |
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| 1.7945 | 30.6 | 100000 | 1.7861 | |
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| 1.7873 | 36.72 | 120000 | 1.7772 | |
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| 1.782 | 42.84 | 140000 | 1.7757 | |
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| 1.7761 | 48.96 | 160000 | 1.7632 | |
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| 1.7714 | 55.08 | 180000 | 1.7685 | |
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| 1.7677 | 61.2 | 200000 | 1.7568 | |
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| 1.7637 | 67.32 | 220000 | 1.7570 | |
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| 1.7585 | 73.44 | 240000 | 1.7442 | |
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| 1.7554 | 79.56 | 260000 | 1.7556 | |
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| 1.7515 | 85.68 | 280000 | 1.7505 | |
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| 1.7483 | 91.8 | 300000 | 1.7463 | |
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| 1.745 | 97.92 | 320000 | 1.7425 | |
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| 1.7427 | 104.04 | 340000 | 1.7425 | |
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| 1.7398 | 110.16 | 360000 | 1.7359 | |
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| 1.7377 | 116.28 | 380000 | 1.7369 | |
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| 1.7349 | 122.4 | 400000 | 1.7340 | |
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| 1.7325 | 128.52 | 420000 | 1.7313 | |
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| 1.731 | 134.64 | 440000 | 1.7256 | |
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| 1.7286 | 140.76 | 460000 | 1.7238 | |
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| 1.7267 | 146.88 | 480000 | 1.7324 | |
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| 1.7247 | 153.0 | 500000 | 1.7247 | |
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| 1.7228 | 159.12 | 520000 | 1.7185 | |
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| 1.7209 | 165.24 | 540000 | 1.7166 | |
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| 1.7189 | 171.36 | 560000 | 1.7206 | |
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| 1.7181 | 177.48 | 580000 | 1.7190 | |
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| 1.7159 | 183.6 | 600000 | 1.7194 | |
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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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