{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/datamafia-at-wnut-2020-task-2-a-study-of-pre","title":"DATAMAFIA at WNUT-2020 Task 2: A Study of Pre-trained Language Models along with Regularization Techniques for Downstream Tasks","arxiv_id":null,"date":"2020-11-01","proceeding":"EMNLP (WNUT) 2020 11","authors":["Ayan Sengupta"],"abstract":"This document describes the system description developed by team datamafia at WNUT-2020 Task 2: Identification of informative COVID-19 English Tweets. This paper contains a thorough study of pre-trained language models on downstream binary classification task over noisy user generated Twitter data. The solution submitted to final test leaderboard is a fine tuned RoBERTa model which achieves F1 score of 90.8% and 89.4% on the dev and test data respectively. In the later part, we explore several techniques for injecting regularization explicitly into language models to generalize predictions over noisy data. Our experiments show that adding regularizations to RoBERTa pre-trained model can be very robust to data and annotation noises and can improve overall performance by more than 1.2%.","url_abs":"https://aclanthology.org/2020.wnut-1.51","url_pdf":"https://aclanthology.org/2020.wnut-1.51.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"datamafia-at-wnut-2020-task-2-a-study-of-pre","repo_url":"https://github.com/victor7246/wnut-2020-task-2","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"binary-classification","task_name":"Binary Classification"},{"task_slug":"task-2","task_name":"Task 2"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}