ARGUABLY@SMM4H’22: Classification of Health Related Tweets using Ensemble, Zero-Shot and Fine-Tuned Language Model

AbstractWith the increase in the use of social media, people have become more outspoken and are using platforms like Reddit, Facebook, and Twitter to express their views and share the medical challenges they are facing. This data is a valuable source of medical insight and is often used for healthcare research. This paper describes our participation in Task 1a, 2a, 2b, 3, 5, 6, 7, and 9 organized by SMM4H 2022. We have proposed two transformer-based approaches to handle the classification tasks. The first approach is fine-tuning single language models. The second approach is ensembling the results of BERT, RoBERTa, and ERNIE 2.0.