Using static vectors with text categorization model #9249
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Hello Spacy community, I have been experimenting with using static word vectors to improve a text categorization model that I made. Since I was not using any word vectors before, I assumed that this should improve my model to some degree. However, after enabling these word vectors, I do not see any significant improvement (nothing above 0.001 increase in any p, r, f score for each of the categories I am training for). My questions are...
For context, I am using GloVe's word vectors. Here are the two config files for both the model without static vectors and with static vectors, respectively. Thank you! |
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Hi! I'm not sure if it's useful to you, but this SO answer also deals with the difference between static & dynamic word vectors. To answer your specific questions:
Yes, I think that's entirely plausible, and yes, it would be the |
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Hi!
I'm not sure if it's useful to you, but this SO answer also deals with the difference between static & dynamic word vectors.
To answer your specific questions:
Yes, I think that's entirely plausible, and yes, it would be the
tok2vec
component that is already learning good vectors. You can sort of "jump start" this learning process by providing static vectors, but it might not help much in accuracy at the end of the training cycle. You might notice a quic…