This report outlines the development of a system that extracts emotions and their associated causes from conversational dialogues. By utilising deep learning techniques and leveraging large pre-trained language models, the model efficiently identifies emotional content within these dialogues. The primary objectives include identifying specific emotions, pinpointing their causes, and understanding their connection. One of the main challenges faced was accurately linking emotions to their precise causes. Nonetheless, the results have been encouraging, demonstrating the model's effectiveness in recognising emotions and their underlying reasons.