FL33TW00D:

One of the most popular papers is linked below but doesn’t use transformers:


Hi @FL33TW00D . Yes Thank you for sharing this paper the objective is to work towards that goal. I am currently trying to identify the weight of the words in the sentence to that particular sentiment/class. For example I am currently using the bart-large-mnli for zero-shot identification of a class(sentiment/intent) in a sentence.
eg: “The service was outstanding but the breakfast was poor”
for class labels ‘Food’ or ‘quality’ gives scores of 0.15 and 0.85 respectively. I want to identify the weight of the words in the sentence that contribute to that score of 0.85 for quality(Which primarily would be ‘service’,‘outstanding’,‘breakfast’,‘poor’). I want to know how I can extract this information assuming it is present in the final layers of the model.
Thank you for you help