To advance Chinese financial natural language processing (NLP), we introduce
BBT-FinT5, a new Chinese financial pre-training language model based on the T5
model. To support this effort, we have built BBT-FinCorpus, a large-scale
financial corpus with approximately 300GB of raw text from four different
sources. In general domain NLP, comprehensive benchmarks like GLUE and
SuperGLUE have driven significant advancements in language model pre-training
by enabling head-to-head comparisons among models. Drawing inspiration from
these benchmarks, we propose BBT-CFLEB, a Chinese Financial Language
understanding and generation Evaluation Benchmark, which includes six datasets
covering both understanding and generation tasks. Our aim is to facilitate
research in the development of NLP within the Chinese financial domain. Our
model, corpus and benchmark are released at
this https URL. Our work belongs to the
Big Bang Transformer (BBT), a large-scale pre-trained language model project.

介绍了基于 T5 模型的新型 BBT-FinT5 中文金融预训练语言模型，同时构建了大规模金融语料库 BBT-FinCorpus 并提出了中文金融语言理解与生成评估基准 BBT-CFLEB 以促进金融领域自然语言处理研究。