
Fine-tuning Pre-trained Language Models for Dialog Act Classification and Sentiment Analysis
This work presents an approach for fine-tuning pre-trained language models to perform dialog act classification or sentiment/emotion analysis.
This work presents an approach for fine-tuning pre-trained language models to perform dialog act classification or sentiment/emotion analysis.
Recent research work has highlighted the growing effectiveness of generative language models in the production of accurate and coherent textual content. By exploiting this technology, this project aimed to develop a system capable of automatically composing questions and answers on predefined topics.