BioLinkBERT-Large-LitCovid-v1.3.1

sofia-todeschini/BioLinkBERT-Large-LitCovid-v1.3.1

BioLinkBERT-Large-LitCovid-v1.3.1 is a text classification model from sofia-todeschini. Use it when you need a label for a piece of text. It is set up for transformers. 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

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Nov 1, 2023
Updated: Nov 2, 2023
SHA: ec36a06b

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Model card

From the Hugging Face model README

BioLinkBERT-Large-LitCovid-v1.3.1c

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

Loss: 1.1423
Hamming loss: 0.0115
F1 micro: 0.8955
F1 macro: 0.5189
F1 weighted: 0.8999
F1 samples: 0.9001
Precision micro: 0.8699
Precision macro: 0.4571
Precision weighted: 0.8797
Precision samples: 0.8987
Recall micro: 0.9228
Recall macro: 0.6461
Recall weighted: 0.9228
Recall samples: 0.9346
Roc Auc: 0.9575
Accuracy: 0.7369

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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Hamming 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
2.3002	1.0	9086	0.8219	0.0155	0.8654	0.4167	0.8761	0.8797	0.8090	0.3554	0.8345	0.8627	0.9302	0.6257	0.9302	0.9414	0.9589	0.6796
1.273	2.0	18172	0.7056	0.0145	0.8730	0.4396	0.8878	0.8898	0.8208	0.3638	0.8526	0.8772	0.9323	0.6919	0.9323	0.9439	0.9604	0.7050
0.8734	3.0	27258	0.8218	0.0123	0.8896	0.4846	0.8969	0.8958	0.8557	0.4219	0.8729	0.8893	0.9264	0.6671	0.9264	0.9378	0.9588	0.7249
0.7889	4.0	36344	0.9218	0.0118	0.8931	0.5037	0.9001	0.8983	0.8651	0.4391	0.8810	0.8966	0.9230	0.6716	0.9230	0.9349	0.9574	0.7333
0.4284	5.0	45430	1.1423	0.0115	0.8955	0.5189	0.8999	0.9001	0.8699	0.4571	0.8797	0.8987	0.9228	0.6461	0.9228	0.9346	0.9575	0.7369

Framework versions

Transformers 4.28.0
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Nov 1, 2023
Updated: Nov 2, 2023