I am trying to build a model for extractive text summarization using keras sequential layers. I am having a hard time trying to understand how to input my x data. Should it be an array of documents with each document containing an array of sentences? or should I further break it down to each sentence containing an array of words?
The y input is basically a binary classification of each sentence to check whether or not they belong to the summary of the document.
The first layer is an embedding layer and I'm using 100d Glove word embedding.
P.s: I am new to machine learning.