Hi!
I am trying to explain BERT. I understand the concept of contextualised embedding, where one word has different embeddings depending on the context. I also understand that when by using bidirectionality, BERT can learn these contextualised embedding during pretraining.
My question is when finetuning BERT for a task and feeding it a sentence, how does BERT know which contextualised embedding to used for the word, given there are several to choose from?