Skip to content

performance is really not that good #37

Open
@wasifmasood

Description

@wasifmasood

Hello team,

thanks a lot for making your contribution open-source. I did some quick tests and got really bad results. E.g., look at the following example where I am measuring cosine distance between "cancer" and "leukemia", got a score of 0.27. Similarly the cosine distance between dog and dobermann is only 0.367. I am doing it the following way:

model = sent2vec.Sent2vecModel() model.load_model(model_path) emb1 = model.embed_sentence("dog") emb2 = model.embed_sentence("dobermann") cosine_similarities = cosine_similarity(emb1, emb2).flatten() print(cosine_similarities)

Can you pls comment whether I am doing something wrong here.

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Type

    No type

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions