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--- |
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license: cc-by-nc-sa-4.0 |
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base_model: InstaDeepAI/nucleotide-transformer-2.5b-1000g |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- accuracy |
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model-index: |
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- name: nucleotide-transformer-2.5b-1000g_ft_Hepg2_1kbpHG19_DHSs_H3K27AC |
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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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# nucleotide-transformer-2.5b-1000g_ft_Hepg2_1kbpHG19_DHSs_H3K27AC |
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This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-2.5b-1000g](https://huggingface.co/InstaDeepAI/nucleotide-transformer-2.5b-1000g) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4911 |
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- F1 Score: 0.8530 |
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- Precision: 0.9084 |
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- Recall: 0.8041 |
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- Accuracy: 0.8470 |
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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: 1e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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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- num_epochs: 3 |
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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 | F1 Score | Precision | Recall | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:| |
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| 0.3896 | 1.8657 | 500 | 0.4911 | 0.8530 | 0.9084 | 0.8041 | 0.8470 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.19.0 |
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