BioLinkBERT – AI Model by zonghaoyang | AlphaNeural AI

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zonghaoyang/
BioLinkBERT

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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BioLinkBERT

This model is a fine-tuned version of michiyasunaga/BioLinkBERT-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6209
Accuracy: 0.8987
F1: 0.5922
Precision: 0.6630
Recall: 0.5351

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.2278	1.0	1626	0.2833	0.9050	0.5842	0.7334	0.4854
0.1896	2.0	3252	0.3267	0.9012	0.6006	0.6752	0.5409
0.144	3.0	4878	0.4336	0.8989	0.6246	0.6376	0.6121
0.1156	4.0	6504	0.4667	0.8939	0.5918	0.6280	0.5595
0.0864	5.0	8130	0.5413	0.8969	0.6103	0.6347	0.5877
0.0515	6.0	9756	0.6209	0.8987	0.5922	0.6630	0.5351

Framework versions

Transformers 4.29.2
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3