Should I normalize SentenceTransformers embeddings?
I’m trying to group text in Spanish based on their semantic similarity, I’m usingSentenceTransformerto obtain the embeddings for my texts but I have a couple of questions:Neither of the models I’m currently using (hiiamsid/sentence_similarity_spanish_es and sentence-transformers/distiluse-base-multilingual-cased-v1) are normalized,SentenceTransformergives me the option to normalize the embeddings, is there any reason to this?Is there any difference in terms of performance between the cosine similarity and the dot score?Why are some models normalized and others are not?