Fraunhofer FKIE @ SMM4H 2022: System Description for Shared Tasks 2, 4 and 9

Daniel Claeser, Samantha Kent


Abstract
We present our results for the shared tasks 2, 4 and 9 at the SMM4H Workshop at COLING 2022 achieved by succesfully fine-tuning pre-trained language models to the downstream tasks. We identify the occurence of code-switching in the test data for task 2 as a possible source of considerable performance degradation on the test set scores. We successfully exploit structural linguistic similarities in the datasets of tasks 4 and 9 for training on joined datasets, scoring first in task 9 and on par with SOTA in task 4.
Anthology ID:
2022.smm4h-1.29
Volume:
Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task
Month:
October
Year:
2022
Address:
Gyeongju, Republic of Korea
Editors:
Graciela Gonzalez-Hernandez, Davy Weissenbacher
Venue:
SMM4H
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
103–107
Language:
URL:
https://aclanthology.org/2022.smm4h-1.29
DOI:
Bibkey:
Cite (ACL):
Daniel Claeser and Samantha Kent. 2022. Fraunhofer FKIE @ SMM4H 2022: System Description for Shared Tasks 2, 4 and 9. In Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task, pages 103–107, Gyeongju, Republic of Korea. Association for Computational Linguistics.
Cite (Informal):
Fraunhofer FKIE @ SMM4H 2022: System Description for Shared Tasks 2, 4 and 9 (Claeser & Kent, SMM4H 2022)
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PDF:
https://aclanthology.org/2022.smm4h-1.29.pdf