In this project, I developed an automated system to evaluate product reviews using OpenAI's GPT-3.5 model. The system assesses review quality by analyzing aspects such as coherence, relevance, and sentiment, providing structured feedback to enhance the reliability of user-generated content.
Data Collection: Compiled a diverse dataset of product reviews to train and evaluate the model.
Model Fine-Tuning: Adapted GPT-3.5 to focus on review evaluation tasks, enhancing its ability to assess review quality.
Evaluation Metrics: Established criteria for review assessment, including coherence, relevance, and sentiment analysis.
Automated Feedback Generation: Implemented a system that provides structured feedback to users, aiming to improve the quality of future reviews.
Deployment: Integrated the evaluation system into a user-friendly interface, allowing seamless interaction for end-users.