[Purpose/significance] The huge quantity and diverse types of red literature bring many difficulties to the fine-grained annotation of red literature, and how to utilize a small amount of existing annotated data to carry out the re⁃search on automated data annotation of red literature is one of the important problems to be solved in the promotion of intelligent processing and application research of red literature. We design the metadata representation system of red literature and try to use transfer learning technology to conduct annotation experiments on unannotated literature to re⁃alize the automated annotation of metadata of red literature.[Method/process] Firstly, BERT-BiLSTM-MHA-CRF model incorporating pre-trained model, bi-directional long and short-term memory network, multi-head attention and conditional random field was constructed. Secondly, according to the content characteristics of red literature, the meta⁃
data representation system of multiple groups of red literature is designed. Finally, the suitability of metadata represen⁃tation systems with transfer learning models in different types of automated red literature annotation tasks was explored.[Result/conclusion] The MRS 6 Metadata Representation System can be used as a metadata representation system for generic red literature. The“BERT-BiLSTM-MHA-CRF + MRS 6”is suitable for the automated annotation of red doc⁃uments in different scenarios, and it has good generalization ability in the automated annotation experiments of the same type of red documents.