dnabert2_ft_BioS73_1kbpHG19_DHSs_H3K27AC_on_shot_one_shot

tanoManzo/dnabert2_ft_BioS73_1kbpHG19_DHSs_H3K27AC_on_shot_one_shot

dnabert2_ft_BioS73_1kbpHG19_DHSs_H3K27AC_on_shot_one_shot is a text classification model from tanoManzo. Use it when you need a label for a piece of text. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Text Classification
Library: transformers
Model type: bert
Access: Public
Created: Oct 29, 2024
Updated: Oct 29, 2024
SHA: 81fb2b2c

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Base models

vivym/DNABERT-2-117M

Model card

From the Hugging Face model README

dnabert2_ft_BioS73_1kbpHG19_DHSs_H3K27AC_on_shot_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: 1.1495
F1 Score: 0.6667
Precision: 0.6667
Recall: 0.6667
Accuracy: 0.7037
Auc: 0.8667
Prc: 0.8708

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
0.3645	18.5185	500	1.1495	0.6667	0.6667	0.6667	0.7037	0.8667	0.8708

Framework versions

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

Task: Text Classification
Library: transformers
Type: bert
Created: Oct 29, 2024
Updated: Oct 29, 2024