This paper presents our models for WNUT2020 shared task2. The shared task2 involves identification of COVID-19 related informative tweets. We treat this as binary text clas-sification problem and experiment with pre-trained language models. Our first model which is based on CT-BERT achieves F1-scoreof 88.7% and second model which is an ensemble of CT-BERT, RoBERTa and SVM achieves F1-score of 88.52%.

In this paper, we present our approach for task1 of SMM4H 2020. This task involves automatic classification of tweets mentioning medication or dietary supplements. For this task, we experiment with pre-trained models like Biomedical RoBERTa, Clinical BERT and Biomedical BERT. Our approach achieves F1-score of 73.56%.