Geneformer_ft_BioS74_1kbpHG19_DHSs_H3K27AC

tanoManzo/Geneformer_ft_BioS74_1kbpHG19_DHSs_H3K27AC

Geneformer_ft_BioS74_1kbpHG19_DHSs_H3K27AC is a machine learning model from tanoManzo. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.

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

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At a glance

License: apache-2.0
Model type: bert
Access: Public
Created: Sep 24, 2024
Updated: Sep 24, 2024
SHA: 9191123b

Base models

ctheodoris/Geneformer

Model card

From the Hugging Face model README

Geneformer_ft_BioS74_1kbpHG19_DHSs_H3K27AC

This model is a fine-tuned version of ctheodoris/Geneformer on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5809
F1 Score: 0.7069
Precision: 0.7107
Recall: 0.7032
Accuracy: 0.6947
Auc: 0.7638
Prc: 0.7611

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
0.6934	0.1314	500	0.6908	0.6505	0.5332	0.8338	0.5309	0.5321	0.5544
0.692	0.2629	1000	0.6811	0.5043	0.6257	0.4224	0.5653	0.6063	0.6190
0.6783	0.3943	1500	0.6729	0.4941	0.6808	0.3877	0.5843	0.6381	0.6423
0.6617	0.5258	2000	0.6570	0.7039	0.5813	0.8920	0.6072	0.6888	0.6876
0.6467	0.6572	2500	0.6336	0.7081	0.6139	0.8363	0.6390	0.7102	0.7119
0.6407	0.7886	3000	0.6094	0.6627	0.7235	0.6113	0.6742	0.7346	0.7343
0.6328	0.9201	3500	0.6017	0.7155	0.6649	0.7745	0.6776	0.7392	0.7450
0.619	1.0515	4000	0.6767	0.5531	0.7975	0.4234	0.6419	0.7419	0.7422
0.6088	1.1830	4500	0.5867	0.7182	0.6960	0.7418	0.6952	0.7564	0.7570
0.6099	1.3144	5000	0.5861	0.7162	0.6959	0.7378	0.6939	0.7557	0.7546
0.6022	1.4458	5500	0.5849	0.6920	0.7243	0.6625	0.6913	0.7602	0.7581
0.582	1.5773	6000	0.5809	0.7069	0.7107	0.7032	0.6947	0.7638	0.7611

Framework versions

Transformers 4.42.3
Pytorch 2.3.0+cu121
Datasets 2.18.0
Tokenizers 0.19.0

Type: bert
License: apache-2.0
Created: Sep 24, 2024
Updated: Sep 24, 2024