A Generic NLI approach for Classification of Sentiment Associated with
  Therapies
Rajaraman Kanagasabai Anitha Veeramani
This paper describes our system for addressing SMM4H 2023 Shared Task 2 on
"Classification of sentiment associated with therapies (aspect-oriented)". In
our work, we adopt an approach based on Natural language inference (NLI) to
formulate this task as a sentence pair classification problem, and train
transformer models to predict sentiment associated with a therapy on a given
text. Our best model achieved 75.22\% F1-score which was 11\% (4\%) more than
the mean (median) score of all teams' submissions.