This paper describes the CASIA’s system for the IWSLT 2020 open domain transla- tion task. This year we participate in both Chinese→Japanese and Japanese→Chinese translation tasks. Our system is neural ma- chine translation system based on Transformer model. We augment the training data with knowledge distillation and back translation to improve the translation performance. Domain data classification and weighted domain model ensemble are introduced to generate the final translation result. We compare and analyze the performance on development data with differ- ent model settings and different data process- ing techniques.