NutCracker at WNUT-2020 Task 2: Robustly Identifying Informative COVID-19 Tweets using Ensembling and Adversarial Training

• URL: http://arxiv.org/abs/2010.04335v1
• Date: Fri, 9 Oct 2020 02:46:51 GMT
• Title: NutCracker at WNUT-2020 Task 2: Robustly Identifying Informative COVID-19 Tweets using Ensembling and Adversarial Training
• Authors: Priyanshu Kumar and Aadarsh Singh
• Abstract summary: We experiment with COVID-Twitter-BERT and RoBERTa models to identify informative COVID-19 tweets. The ensemble of COVID-Twitter-BERT and RoBERTa obtains a F1-score of 0.9096 on the test data of WNUT-2020 Task 2 and ranks 1st on the leaderboard.
• Score: 6.85316573653194
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We experiment with COVID-Twitter-BERT and RoBERTa models to identify informative COVID-19 tweets. We further experiment with adversarial training to make our models robust. The ensemble of COVID-Twitter-BERT and RoBERTa obtains a F1-score of 0.9096 (on the positive class) on the test data of WNUT-2020 Task 2 and ranks 1st on the leaderboard. The ensemble of the models trained using adversarial training also produces similar result.

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