1. A sequence tagging system that provides for transfer learning, the sequence tagging system comprising: a computing device including a processing unit and a memory, the processing unit implementing a first hidden layered conditional random field (HCRF) model, the first HCRF model comprises a pre-training system and a first training system, the pre-training system is operable to: obtain unlabeled data; run a word clustering algorithm on the unlabeled data to generate word clusters; determine a pseudo-label for each input of the unlabeled data based on the word clusters to form pseudo-labeled data; extract pre-training features from the pseudo-labeled data, and estimate pre-training model parameters for the pre-training features utilizing a first training algorithm, wherein the pre-training model parameters are stored in a first hidden layer of the first HCRF model; the first training system is operable to: obtain a first set of labeled data for a first specific task; estimate first task specific model parameters based on a second training algorithm that is initialized utilizing the pre-training model parameters.