Text Classification

Text Classification is a core task in natural language processing, aimed at categorizing text data into predefined categories. This task achieves efficient information organization and retrieval by analyzing the content of the text and identifying its features such as topic, sentiment, or intent. In recent years, deep learning models like XLNet and RoBERTa have significantly improved the performance of text classification, driving technological advancements. Benchmark datasets such as GLUE and AGNews are widely used to evaluate the effectiveness of these models.