Chinese text summarization based on fine-tuned GPT2

Pre-trained language model has a good performance in text summarization task, thus we present a neural text summarization based on a powerful pre-trained language model GPT-2. In this paper, we propose a Chinese text summarization model by extending into our downstream task to acquire relevant, contentful, and coherent summarization. By extensive experiments, our model achieves absolute improvements of 10.75% on ROUGE-1, 13.85% on ROUGE-2, and 9.73% on ROUGE-L on the LCSTS datasets. Compared with the state-of-the-art summarization model, e.g. BERTSUM based model, our model also achieves an improvement of 25.22% on ROUGE-1.