BioLinkBERT-LitCovid-v1.2.1 – AI Model by sofia-todeschini | AlphaNeural AI

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sofia-todeschini/
BioLinkBERT-LitCovid-v1.2.1

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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BioLinkBERT-LitCovid-v1.2.1

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: 0.2205
F1 micro: 0.9016
F1 macro: 0.8505
F1 weighted: 0.9044
F1 samples: 0.9056
Precision micro: 0.8545
Precision macro: 0.7857
Precision weighted: 0.8625
Precision samples: 0.8862
Recall micro: 0.9540
Recall macro: 0.9431
Recall weighted: 0.9540
Recall samples: 0.9610
Roc Auc: 0.9578
Accuracy: 0.7211

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: 4

Training results

Training Loss	Epoch	Step	Validation Loss	F1 micro	F1 macro	F1 weighted	F1 samples	Precision micro	Precision macro	Precision weighted	Precision samples	Recall micro	Recall macro	Recall weighted	Recall samples	Roc Auc	Accuracy
0.2839	1.0	2211	0.2205	0.9016	0.8505	0.9044	0.9056	0.8545	0.7857	0.8625	0.8862	0.9540	0.9431	0.9540	0.9610	0.9578	0.7211
0.1926	2.0	4422	0.2477	0.9134	0.8734	0.9147	0.9159	0.8770	0.8309	0.8808	0.9026	0.9529	0.9283	0.9529	0.9590	0.9607	0.7554
0.1341	3.0	6633	0.2667	0.9155	0.8749	0.9164	0.9170	0.8823	0.8328	0.8851	0.9059	0.9513	0.9251	0.9513	0.9569	0.9606	0.7642
0.1161	4.0	8844	0.2864	0.9188	0.8783	0.9195	0.9202	0.8938	0.8451	0.8958	0.9150	0.9452	0.9173	0.9452	0.9525	0.9593	0.7758

Framework versions

Transformers 4.28.0
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3