Chinese Sentiment Classification Model based on Pre-Trained BERT
Jie Gao · 2021
In order to solve the problems of low accuracy, less training data and poor training results of traditional machine learning algorithm in Chinese sentient classification task, this paper proposes a Chinese sentient classification model based on pre trained BERT. After pre training for Bert using large-scale unlabeled corpus, the Bert model can extract the text abstract features of a single Chinese character based on the context semantic relationship. Then we combine the text abstract features with the whole sentence's semantic vector and send them to the softmax classifier to form a Chinese sentient classification model for training and fine tuning. The model performs well in multiple open source Chinese sentient classification datasets, which indicates that the model can complete Chinese sentient classification task well.