@inproceedings{guo-etal-2021-pre,
title = "Pre-trained Transformer-based Classification and Span Detection Models for Social Media Health Applications",
author = "Guo, Yuting and
Ge, Yao and
Ali Al-Garadi, Mohammed and
Sarker, Abeed",
editor = "Magge, Arjun and
Klein, Ari and
Miranda-Escalada, Antonio and
Al-garadi, Mohammed Ali and
Alimova, Ilseyar and
Miftahutdinov, Zulfat and
Farre-Maduell, Eulalia and
Lopez, Salvador Lima and
Flores, Ivan and
O'Connor, Karen and
Weissenbacher, Davy and
Tutubalina, Elena and
Sarker, Abeed and
Banda, Juan M and
Krallinger, Martin and
Gonzalez-Hernandez, Graciela",
booktitle = "Proceedings of the Sixth Social Media Mining for Health ({\#}SMM4H) Workshop and Shared Task",
month = jun,
year = "2021",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.smm4h-1.8/",
doi = "10.18653/v1/2021.smm4h-1.8",
pages = "52--57",
abstract = "This paper describes our approach for six classification tasks (Tasks 1a, 3a, 3b, 4 and 5) and one span detection task (Task 1b) from the Social Media Mining for Health (SMM4H) 2021 shared tasks. We developed two separate systems for classification and span detection, both based on pre-trained Transformer-based models. In addition, we applied oversampling and classifier ensembling in the classification tasks. The results of our submissions are over the median scores in all tasks except for Task 1a. Furthermore, our model achieved first place in Task 4 and obtained a 7{\%} higher F1-score than the median in Task 1b."
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%0 Conference Proceedings
%T Pre-trained Transformer-based Classification and Span Detection Models for Social Media Health Applications
%A Guo, Yuting
%A Ge, Yao
%A Ali Al-Garadi, Mohammed
%A Sarker, Abeed
%Y Magge, Arjun
%Y Klein, Ari
%Y Miranda-Escalada, Antonio
%Y Al-garadi, Mohammed Ali
%Y Alimova, Ilseyar
%Y Miftahutdinov, Zulfat
%Y Farre-Maduell, Eulalia
%Y Lopez, Salvador Lima
%Y Flores, Ivan
%Y O’Connor, Karen
%Y Weissenbacher, Davy
%Y Tutubalina, Elena
%Y Sarker, Abeed
%Y Banda, Juan M.
%Y Krallinger, Martin
%Y Gonzalez-Hernandez, Graciela
%S Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task
%D 2021
%8 June
%I Association for Computational Linguistics
%C Mexico City, Mexico
%F guo-etal-2021-pre
%X This paper describes our approach for six classification tasks (Tasks 1a, 3a, 3b, 4 and 5) and one span detection task (Task 1b) from the Social Media Mining for Health (SMM4H) 2021 shared tasks. We developed two separate systems for classification and span detection, both based on pre-trained Transformer-based models. In addition, we applied oversampling and classifier ensembling in the classification tasks. The results of our submissions are over the median scores in all tasks except for Task 1a. Furthermore, our model achieved first place in Task 4 and obtained a 7% higher F1-score than the median in Task 1b.
%R 10.18653/v1/2021.smm4h-1.8
%U https://aclanthology.org/2021.smm4h-1.8/
%U https://doi.org/10.18653/v1/2021.smm4h-1.8
%P 52-57
Markdown (Informal)
[Pre-trained Transformer-based Classification and Span Detection Models for Social Media Health Applications](https://aclanthology.org/2021.smm4h-1.8/) (Guo et al., SMM4H 2021)
ACL