CIA_NITT at WNUT-2020 Task 2: Classification of COVID-19 Tweets Using Pre-trained Language Models
This work addresses the need for filtering relevant COVID-19 information on social media, but it is incremental as it applies existing pre-trained models to a new dataset.
The paper tackled the problem of identifying COVID-19 related informative tweets as a binary text classification task, achieving F1-scores of 88.7% with a CT-BERT model and 88.52% with an ensemble model.
This paper presents our models for WNUT 2020 shared task2. The shared task2 involves identification of COVID-19 related informative tweets. We treat this as binary text classification problem and experiment with pre-trained language models. Our first model which is based on CT-BERT achieves F1-score of 88.7% and second model which is an ensemble of CT-BERT, RoBERTa and SVM achieves F1-score of 88.52%.