Transformer Model Applications: A Comprehensive Survey and Analysis

Transformer models have risen as a powerful tool in natural language processing (NLP), demonstrating outstanding performance across a diverse array of tasks. This research paper provides a comprehensive survey and analysis of transformer model applications, covering various domains and tasks. It explores the impact of transformers in text generation, sentiment analysis, machine translation, document classification, question-answering, and many more. Here, we discusses the architecture, training strategies, and specific adaptations of transformers for each application. Furthermore, the challenges, limitations, and future directions for transformer model applications are highlighted.