每年專案
摘要
This study describes our proposed model design for SMM4H 2021 shared tasks. We fine-tune the language model of RoBERTa transformers and their connecting classifier to complete the classification tasks of tweets for adverse pregnancy outcomes (Task 4) and potential COVID-19 cases (Task 5). The evaluation metric is F1-score of the positive class for both tasks. For Task 4, our best score of 0.93 exceeded the median score of 0.925. For Task 5, our best of 0.75 exceeded the median score of 0.745.
原文 | ???core.languages.en_GB??? |
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主出版物標題 | Social Media Mining for Health, SMM4H 2021 - Proceedings of the 6th Workshop and Shared Tasks |
編輯 | Arjun Magge, Ari Z. Klein, Antonio Miranda-Escalada, Mohammed Ali Al-garadi, Ilseyar Alimova, Zulfat Miftahutdinov, Eulalia Farre-Maduell, Salvador Lima Lopez, Ivan Flores, Karen O'Connor, Davy Weissenbacher, Elena Tutubalina, Abeed Sarker, Juan M Banda, Martin Krallinger, Graciela Gonzalez-Hernandez |
發行者 | Association for Computational Linguistics (ACL) |
頁面 | 98-101 |
頁數 | 4 |
ISBN(電子) | 9781954085312 |
出版狀態 | 已出版 - 2021 |
事件 | 6th Workshop and Shared Tasks on Social Media Mining for Health, SMM4H 2021 - Mexico City, Mexico 持續時間: 10 6月 2021 → … |
出版系列
名字 | Social Media Mining for Health, SMM4H 2021 - Proceedings of the 6th Workshop and Shared Tasks |
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???event.eventtypes.event.conference??? | 6th Workshop and Shared Tasks on Social Media Mining for Health, SMM4H 2021 |
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國家/地區 | Mexico |
城市 | Mexico City |
期間 | 10/06/21 → … |
指紋
深入研究「Classification of Tweets Self-reporting Adverse Pregnancy Outcomes and Potential COVID-19 Cases Using RoBERTa Transformers」主題。共同形成了獨特的指紋。專案
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