Question Answering System using BERT

Question Answering System (QA system) is a task that involves identifying the answers to the

questions from a large corpus of text. It involves various information such as information

retrieval, text understanding, and extracting the information to answer the questions

accurately based on the meaning of the input and the context. There are two types of QA

system which is extracting answer from the input / given context and generating an answer

from the context that answers the questions correctly. The QA system will be implemented

using BERT transformer using SQuAD dataset.

In QA system, the trained model should understand the questions’ meaning and the to

differentiate between words. Also retrieving the needed information from large data. For

accurate answers, the model should understand how to represent the answers data by using

word tokenization and analyze the data. In the final step, the model should validate the answer

accuracy.