A Brief Overview on SQuAD2.0: Stanford Question Answering Dataset (SQuAD) is simply a reading comprehension dataset which is nowadays used to train machine learning models.
The dataset consists of questions raised over a certain paragraph by a community of crowd workers through Wikipedia articles. The answers to these questions can be derived from the corresponding paragraphs, and there are chances for unanswerable questions too.
Now, let’s look into What users can get out of the Squad
SQuAD2.0 comes with the combination of 100,000 answerable questions from SQuAD1.1 and the additional 50,000 unanswerable opposed questions. These unanswerable adversary questions are raised more similar to those of the answerable ones. So in order to perform excellently on SQuAD2.0, the trained machine learning systems must not only answer the answerable questions but also have to decide in no time whether the specific question can be answered or not from the given paragraph.If found unanswerable, it should quickly switch to the other question pointing that particular question is unanswerable from the paragraph.
This is the icebreaking significance of SQuAD 2.0. It trains the machine learning models not only to answer the questions from reading comprehension but also to abstain from unanswerable questions or adversities of the real world.