Research on the application of deep learning-based bert model in sentiment analysis

HIGHLIGHTS

• What: This research explores the application of Deep Learning-based BERT models particularly DistilBERT in sentiment analysis. From the name, the goal of the BERT model is to use large-scale unlabeled corpus to train and obtain a Representation of a text containing rich semantic information, that is, a semantic representation of the text, and then fine-tune the semantic representation of the text in a specific NLP task, and finally apply it to that NLP task. In this experiment, the authors will use the SST2 dataset as training and test data to evaluate the performance of . . .
  

   

  

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