Comment from Chuan Jiang on BERT Document Classification Tutorial with Code:
For the comment you made that embedding can only make sense unless model has been fine-tuned. However to do so we have to have training data with labels to fine tune it at the beginning. Otherwise, how can I compare semantic embedding for the following two texts (presumably similar) in a unsupervised way?
(1) What’s the population of US?
(2) How many US citizens are there in US?