Introduction: Applications of BERT

In this section, we'll learn how to fine-tune BERT for text summarization tasks using BERTSUM. Then, we will explore how to apply BERT for languages other than English. We will also learn about VideoBERT and other interesting models.

The following chapters are included in this section:

• Exploring BERTSUM for Text Summarization

• Applying BERT to Other Languages

• Exploring Sentence and Domain-Specific BERT

• Working with VideoBERT, BART, and More

Exploring BERTSUM for text summarization

Text summarization is one of the most popular applications of natural language processing. This chapter will explain how to fine-tune the pre-trained BERT model for a text summarization task. The BERT model fine-tuned for the text summarization task is often called BERTSUM (BERT for summarization). We will understand what BERTSUM is and how it is used for text summarization in detail.

We will begin by understanding two different types of text summarization—extractive and abstractive summarizations. First, we will learn how to perform extractive summarization using BERTSUM with a classifier, BERTSUM with a transformer, and BERTSUM with an LSTM. Next, we will look into how BERTSUM is used for performing the abstractive summarization task.