ISLab System for SMM4H Shared Task 2020
Chen-Kai Wang | Hong-Jie Dai | You-Chen Zhang | Bo-Chun Xu | Bo-Hong Wang | You-Ning Xu | Po-Hao Chen | Chung-Hong Lee
Proceedings of the Fifth Social Media Mining for Health Applications Workshop & Shared Task
In this paper, we described our systems for the first and second subtasks of Social Media Mining for Health Applications (SMM4H) shared task in 2020. The two subtasks are automatic classi-fication of medication mentions and adverse effect in tweets. Our systems for both subtasks are based on Robustly optimized BERT approach (RoBERTa) and our previous work at SMM4H’19. The best F1-scores achieved by our systems for subtask 1 and 2 were 0.7974 and 0.64 respec-tively, which outperformed the average F1-scores among all teams’ best runs by at least 0.13.