Evaluating Large Language Models for Anxiety and Depression Classification using Counseling and Psychotherapy Transcripts

Code

• github.com/ivysun14/mental-health-prediction
  OfficialIn paperpytorch★ 4

Abstract

We aim to evaluate the efficacy of traditional machine learning and large language models (LLMs) in classifying anxiety and depression from long conversational transcripts. We fine-tune both established transformer models (BERT, RoBERTa, Longformer) and more recent large models (Mistral-7B), trained a Support Vector Machine with feature engineering, and assessed GPT models through prompting. We observe that state-of-the-art models fail to enhance classification outcomes compared to traditional machine learning methods.

Tasks

Reproductions