AAST-NLP@#SMM4H’24: Finetuning Language Models for Exact Age Classification and Effect of Outdoor Spaces on Social Anxiety

AbstractThis paper evaluates the performance of “AAST-NLP” in the Social Media Mining for Health (SMM4H) Shared Tasks 3 and 6, where more than 20 teams participated in each. We leveraged state-of-the-art transformer-based models, including Mistral, to achieve our results. Our models consistently outperformed both the mean and median scores across the tasks. Specifically, an F1-score of 0.636 was achieved in classifying the impact of outdoor spaces on social anxiety symptoms, while an F1-score of 0.946 was recorded for the classification of self-reported exact ages.