LHS712NV at #SMM4H 2024 Task 4: Using BERT to classify Reddit posts on non-medical substance use

Valeria Fraga, Neha Nair, Dalton Simancek, V.G.Vinod Vydiswaran


Abstract
This paper summarizes our participation in the Shared Task 4 of #SMM4H 2024. Task 4 was a named entity recognition (NER) task identifying clinical and social impacts of non-medical substance use in English Reddit posts. We employed the Bidirectional Encoder Representations from Transformers (BERT) model to complete this task. Our team achieved an F1-score of 0.892 on a validation set and a relaxed F1-score of 0.191 on the test set.
Anthology ID:
2024.smm4h-1.34
Volume:
Proceedings of The 9th Social Media Mining for Health Research and Applications (SMM4H 2024) Workshop and Shared Tasks
Month:
August
Year:
2024
Address:
Bangkok, Thailand
Editors:
Dongfang Xu, Graciela Gonzalez-Hernandez
Venues:
SMM4H | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
146–148
Language:
URL:
https://aclanthology.org/2024.smm4h-1.34
DOI:
Bibkey:
Cite (ACL):
Valeria Fraga, Neha Nair, Dalton Simancek, and V.G.Vinod Vydiswaran. 2024. LHS712NV at #SMM4H 2024 Task 4: Using BERT to classify Reddit posts on non-medical substance use. In Proceedings of The 9th Social Media Mining for Health Research and Applications (SMM4H 2024) Workshop and Shared Tasks, pages 146–148, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):
LHS712NV at #SMM4H 2024 Task 4: Using BERT to classify Reddit posts on non-medical substance use (Fraga et al., SMM4H-WS 2024)
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PDF:
https://preview.aclanthology.org/nschneid-patch-4/2024.smm4h-1.34.pdf