README.md

metadata

library_name: transformers
base_model: vivym/DNABERT-2-117M
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - accuracy
model-index:
  - name: dnabert2_ft_BioS73_1kbpHG19_DHSs_H3K27AC_one_shot
    results: []

dnabert2_ft_BioS73_1kbpHG19_DHSs_H3K27AC_one_shot

This model is a fine-tuned version of vivym/DNABERT-2-117M on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.1417
• F1 Score: 0.7692
• Precision: 0.7143
• Recall: 0.8333
• Accuracy: 0.7778
• Auc: 0.85
• Prc: 0.8533

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: 8
• eval_batch_size: 8
• 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
0.3716	18.5185	500	1.1417	0.7692	0.7143	0.8333	0.7778	0.85	0.8533

Framework versions

• Transformers 4.46.0.dev0
• Pytorch 2.4.1+cu121
• Datasets 2.18.0
• Tokenizers 0.20.0