Good morning/evening
I am trying to understand how does distilbart generate summaries, like what is the logic behind when you fine tune it with texts and their reference summaries, how does it learn to summarize with a specified length with new words? The way I see it is: I feed a text into the model, it gets encoded & then decoded with only the tokens containing important information? How does the model spots kinda the good sentences tokens?