dnabert2_ft_BioS45_1kbpHG19_DHSs_H3K27AC

tanoManzo/dnabert2_ft_BioS45_1kbpHG19_DHSs_H3K27AC

dnabert2_ft_BioS45_1kbpHG19_DHSs_H3K27AC 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: Sep 29, 2024
Updated: Sep 29, 2024
SHA: f43c23bc

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Base models

vivym/DNABERT-2-117M

Model card

From the Hugging Face model README

dnabert2_ft_BioS45_1kbpHG19_DHSs_H3K27AC

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: 0.5078
F1 Score: 0.7689
Precision: 0.7637
Recall: 0.7742
Accuracy: 0.7573
Auc: 0.8450
Prc: 0.8391

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
0.5979	0.2103	500	0.5225	0.7257	0.7730	0.6839	0.7303	0.8242	0.8198
0.5569	0.4207	1000	0.4987	0.7738	0.7492	0.8	0.7560	0.8369	0.8319
0.5311	0.6310	1500	0.6019	0.7551	0.6133	0.9823	0.6676	0.8369	0.8350
0.5364	0.8414	2000	0.5073	0.7705	0.7693	0.7718	0.7602	0.8422	0.8364
0.5181	1.0517	2500	0.4907	0.7677	0.7575	0.7782	0.7543	0.8440	0.8378
0.521	1.2621	3000	0.5623	0.7869	0.7176	0.8710	0.7539	0.8428	0.8383
0.5122	1.4724	3500	0.5053	0.7525	0.7899	0.7185	0.7535	0.8442	0.8382
0.5096	1.6828	4000	0.5218	0.7811	0.7504	0.8145	0.7619	0.8463	0.8389
0.5031	1.8931	4500	0.4943	0.7814	0.7358	0.8331	0.7568	0.8409	0.8379
0.4983	2.1035	5000	0.5559	0.7797	0.7438	0.8194	0.7585	0.8385	0.8371
0.4792	2.3138	5500	0.5078	0.7689	0.7637	0.7742	0.7573	0.8450	0.8391

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: Sep 29, 2024
Updated: Sep 29, 2024