|
--- |
|
license: bsd-3-clause |
|
base_model: LongSafari/hyenadna-medium-450k-seqlen-hf |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- precision |
|
- recall |
|
- accuracy |
|
model-index: |
|
- name: hyenadna-medium-450k-seqlen-hf_ft_BioS74_1kbpHG19_DHSs_H3K27AC |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# hyenadna-medium-450k-seqlen-hf_ft_BioS74_1kbpHG19_DHSs_H3K27AC |
|
|
|
This model is a fine-tuned version of [LongSafari/hyenadna-medium-450k-seqlen-hf](https://huggingface.co/LongSafari/hyenadna-medium-450k-seqlen-hf) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4642 |
|
- F1 Score: 0.8034 |
|
- Precision: 0.7730 |
|
- Recall: 0.8363 |
|
- Accuracy: 0.7857 |
|
- Auc: 0.8626 |
|
- Prc: 0.8590 |
|
|
|
## Model description |
|
|
|
More information needed |
|
|
|
## Intended uses & limitations |
|
|
|
More information needed |
|
|
|
## Training and evaluation data |
|
|
|
More information needed |
|
|
|
## Training procedure |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 1e-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 20 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | F1 Score | Precision | Recall | Accuracy | Auc | Prc | |
|
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|:------:|:------:| |
|
| 0.5486 | 0.2629 | 500 | 0.5108 | 0.7728 | 0.7601 | 0.7860 | 0.7581 | 0.8210 | 0.8101 | |
|
| 0.4949 | 0.5258 | 1000 | 0.4955 | 0.7852 | 0.7800 | 0.7906 | 0.7736 | 0.8368 | 0.8242 | |
|
| 0.4746 | 0.7886 | 1500 | 0.4766 | 0.7948 | 0.7728 | 0.8182 | 0.7789 | 0.8464 | 0.8356 | |
|
| 0.4782 | 1.0515 | 2000 | 0.4691 | 0.7927 | 0.7933 | 0.7921 | 0.7831 | 0.8544 | 0.8480 | |
|
| 0.4619 | 1.3144 | 2500 | 0.4738 | 0.8016 | 0.7614 | 0.8463 | 0.7807 | 0.8506 | 0.8398 | |
|
| 0.45 | 1.5773 | 3000 | 0.4861 | 0.8063 | 0.7462 | 0.8769 | 0.7794 | 0.8530 | 0.8446 | |
|
| 0.4429 | 1.8402 | 3500 | 0.4836 | 0.7840 | 0.8013 | 0.7675 | 0.7786 | 0.8553 | 0.8508 | |
|
| 0.4459 | 2.1030 | 4000 | 0.4606 | 0.8006 | 0.7833 | 0.8187 | 0.7865 | 0.8616 | 0.8588 | |
|
| 0.413 | 2.3659 | 4500 | 0.4687 | 0.7903 | 0.7931 | 0.7875 | 0.7812 | 0.8600 | 0.8572 | |
|
| 0.4162 | 2.6288 | 5000 | 0.4616 | 0.8036 | 0.7786 | 0.8302 | 0.7875 | 0.8600 | 0.8555 | |
|
| 0.4196 | 2.8917 | 5500 | 0.4642 | 0.8034 | 0.7730 | 0.8363 | 0.7857 | 0.8626 | 0.8590 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.42.3 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.19.0 |
|
|
