UCCNLP@SMM4H’22:Label distribution aware long-tailed learning with post-hoc posterior calibration applied to text classification
| dc.contributor.author | Trust, Paul | |
| dc.contributor.author | Kadusabe, Provia | |
| dc.contributor.author | Zahran, Ahmed | |
| dc.contributor.author | Minghim, Rosane | |
| dc.contributor.author | Omala, Kizito | |
| dc.contributor.funder | Science Foundation Ireland | en |
| dc.date.accessioned | 2022-11-09T09:37:06Z | |
| dc.date.available | 2022-11-09T09:37:06Z | |
| dc.date.issued | 2022-10 | |
| dc.date.updated | 2022-10-20T09:15:42Z | |
| dc.description.abstract | The paper describes our submissions for the Social Media Mining for Health (SMM4H) workshop 2022 shared tasks. We participated in 2 tasks: (1) classification of adverse drug events (ADE) mentions in english tweets (Task-1a) and (2) classification of self-reported intimate partner violence (IPV) on twitter (Task 7). We proposed an approach that uses RoBERTa (A Robustly Optimized BERT Pretraining Approach) fine-tuned with a label distribution-aware margin loss function and post-hoc posterior calibration for robust inference against class imbalance. We achieved a 4% and 1 % increase in performance on IPV and ADE respectively when compared with the traditional fine-tuning strategy with unweighted cross-entropy loss. | en |
| dc.description.status | Not peer reviewed | en |
| dc.description.version | Published Version | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Trust, P., Kadusabe, P., Zahran, A., Minghim, R. and Omala, K. (2022) 'UCCNLP@SMM4H’22:Label distribution aware long-tailed learning with post-hoc posterior calibration applied to text classification', Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task, Gyeongju, Republic of Korea, 12-17 October, pp. 90-94. Available at: https://aclanthology.org/2022.smm4h-1.26.pdf (Accessed: 9 November 2022) | en |
| dc.identifier.endpage | 94 | en |
| dc.identifier.startpage | 90 | en |
| dc.identifier.uri | https://hdl.handle.net/10468/13838 | |
| dc.language.iso | en | en |
| dc.publisher | Association for Computational Linguistics | en |
| dc.relation.uri | https://aclanthology.org/2022.smm4h-1.26 | |
| dc.rights | © 2022, the Authors. This paper is distributed under the terms of the Creative Commons Attribution Licence 4.0. | en |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en |
| dc.subject | Social Media Mining for Health | en |
| dc.title | UCCNLP@SMM4H’22:Label distribution aware long-tailed learning with post-hoc posterior calibration applied to text classification | en |
| dc.type | Conference item | en |
