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--- |
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license: apache-2.0 |
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base_model: ctheodoris/Geneformer |
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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: Geneformer_ft_BioS45_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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# Geneformer_ft_BioS45_1kbpHG19_DHSs_H3K27AC |
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This model is a fine-tuned version of [ctheodoris/Geneformer](https://huggingface.co/ctheodoris/Geneformer) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6631 |
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- F1 Score: 0.5409 |
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- Precision: 0.6586 |
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- Recall: 0.4589 |
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- Accuracy: 0.5936 |
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- Auc: 0.6567 |
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- Prc: 0.6689 |
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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: 20 |
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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 | Auc | Prc | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|:------:|:------:| |
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| 0.6972 | 0.2103 | 500 | 0.6987 | 0.0 | 0.0 | 0.0 | 0.4783 | 0.5304 | 0.5397 | |
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| 0.6932 | 0.4207 | 1000 | 0.6899 | 0.6877 | 0.5307 | 0.9766 | 0.5372 | 0.5631 | 0.5685 | |
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| 0.6931 | 0.6310 | 1500 | 0.6869 | 0.4327 | 0.6091 | 0.3355 | 0.5410 | 0.5889 | 0.5992 | |
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| 0.6827 | 0.8414 | 2000 | 0.6669 | 0.6767 | 0.5763 | 0.8194 | 0.5915 | 0.6392 | 0.6453 | |
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| 0.6667 | 1.0517 | 2500 | 0.6631 | 0.5409 | 0.6586 | 0.4589 | 0.5936 | 0.6567 | 0.6689 | |
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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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