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--- |
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license: cc-by-nc-sa-4.0 |
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base_model: InstaDeepAI/nucleotide-transformer-500m-human-ref |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- matthews_correlation |
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- accuracy |
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model-index: |
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- name: mus_promoter-finetuned-lora-500m-human-ref |
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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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# mus_promoter-finetuned-lora-500m-human-ref |
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This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-500m-human-ref](https://huggingface.co/InstaDeepAI/nucleotide-transformer-500m-human-ref) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4605 |
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- F1: 0.9444 |
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- Matthews Correlation: 0.8749 |
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- Accuracy: 0.9375 |
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- F1 Score: 0.9444 |
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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: 0.0005 |
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- train_batch_size: 8 |
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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: 1000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Matthews Correlation | Accuracy | F1 Score | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------:|:--------:|:--------:| |
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| 0.7975 | 0.43 | 100 | 0.3190 | 0.9231 | 0.8108 | 0.9062 | 0.9231 | |
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| 0.3818 | 0.85 | 200 | 0.2951 | 0.9167 | 0.8113 | 0.9062 | 0.9167 | |
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| 0.3829 | 1.28 | 300 | 0.5043 | 0.9 | 0.7507 | 0.875 | 0.9 | |
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| 0.2565 | 1.71 | 400 | 0.2655 | 0.9351 | 0.8414 | 0.9219 | 0.9351 | |
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| 0.2098 | 2.14 | 500 | 0.3518 | 0.9333 | 0.8395 | 0.9219 | 0.9333 | |
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| 0.1841 | 2.56 | 600 | 0.2601 | 0.9211 | 0.8076 | 0.9062 | 0.9211 | |
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| 0.0804 | 2.99 | 700 | 0.3953 | 0.9315 | 0.8411 | 0.9219 | 0.9315 | |
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| 0.0463 | 3.42 | 800 | 0.4732 | 0.9444 | 0.8749 | 0.9375 | 0.9444 | |
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| 0.057 | 3.85 | 900 | 0.4799 | 0.9444 | 0.8749 | 0.9375 | 0.9444 | |
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| 0.0144 | 4.27 | 1000 | 0.4605 | 0.9444 | 0.8749 | 0.9375 | 0.9444 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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