NutCracker at WNUT-2020 Task 2: Robustly Identifying Informative COVID-19 Tweets using Ensembling and Adversarial Training
Priyanshu Kumar, Aadarsh Singh
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.
Results
| Task | Dataset | Metric | Value | Model |
|---|---|---|---|---|
| Text Classification | WNUT-2020 Task 2 | F1 | 0.9096 | NutCracker |
| Classification | WNUT-2020 Task 2 | F1 | 0.9096 | NutCracker |
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