nucleotide-transformer-v2-250m-multi-species_ft_BioS2_1kbpHG19_DHSs_H3K27AC_one_shot – AI Model by tanoManzo | AlphaNeural AI

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tanoManzo/
nucleotide-transformer-v2-250m-multi-species_ft_BioS2_1kbpHG19_DHSs_H3K27AC_one_shot

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text-classification

generated_from_trainer

InstaDeepAI/nucleotide-transformer-v2-250m-multi-species

cc-by-nc-sa-4.0

autotrain_compatible

endpoints_compatible

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nucleotide-transformer-v2-250m-multi-species_ft_BioS2_1kbpHG19_DHSs_H3K27AC_one_shot

This model is a fine-tuned version of InstaDeepAI/nucleotide-transformer-v2-250m-multi-species on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7399
F1 Score: 0.8084
Precision: 0.8006
Recall: 0.8164
Accuracy: 0.8013
Auc: 0.8735
Prc: 0.8637

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: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Score	Precision	Recall	Accuracy	Auc	Prc
0.5348	0.8403	500	0.4797	0.7964	0.7422	0.8590	0.7744	0.8621	0.8383
0.3808	1.6807	1000	0.5203	0.7973	0.8081	0.7869	0.7946	0.8683	0.8507
0.2366	2.5210	1500	0.7399	0.8084	0.8006	0.8164	0.8013	0.8735	0.8637

Framework versions

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