BioLinkBERT-LitCovid-v1.3.1

sofia-todeschini/BioLinkBERT-LitCovid-v1.3.1

BioLinkBERT-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 1, 2023
SHA: eb2168c8

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Model card

From the Hugging Face model README

BioLinkBERT-LitCovid-v1.3.1

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: 0.6883
Hamming loss: 0.0171
F1 micro: 0.8542
F1 macro: 0.3828
F1 weighted: 0.8818
F1 samples: 0.8804
Precision micro: 0.7855
Precision macro: 0.3067
Precision weighted: 0.8407
Precision samples: 0.8641
Recall micro: 0.9360
Recall macro: 0.7145
Recall weighted: 0.9360
Recall samples: 0.9459
Roc Auc: 0.9607
Accuracy: 0.6896

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: 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
1.0638	1.0	2272	0.4414	0.0398	0.7141	0.2594	0.8318	0.8178	0.5807	0.2077	0.7729	0.7843	0.9269	0.8062	0.9269	0.9422	0.9445	0.5545
0.8571	2.0	4544	0.4364	0.0230	0.8122	0.3367	0.8645	0.8517	0.7236	0.2666	0.8255	0.8284	0.9254	0.7835	0.9254	0.9396	0.9527	0.6211
0.6709	3.0	6816	0.4827	0.0218	0.8222	0.3405	0.8723	0.8638	0.7297	0.2708	0.8239	0.8381	0.9415	0.7770	0.9415	0.9513	0.9609	0.6488
0.5093	4.0	9088	0.5695	0.0184	0.8457	0.3795	0.8781	0.8753	0.7692	0.3006	0.8333	0.8556	0.9390	0.7605	0.9390	0.9482	0.9615	0.6760
0.2957	5.0	11360	0.6883	0.0171	0.8542	0.3828	0.8818	0.8804	0.7855	0.3067	0.8407	0.8641	0.9360	0.7145	0.9360	0.9459	0.9607	0.6896

Framework versions

Transformers 4.28.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.13.3

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