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Details on word2vec model #10

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PhilKuhnke opened this issue Oct 15, 2017 · 1 comment
Open

Details on word2vec model #10

PhilKuhnke opened this issue Oct 15, 2017 · 1 comment

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@PhilKuhnke
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PhilKuhnke commented Oct 15, 2017

Dear Kyubyong,
great work - thank you very much for proving these word vectors!
One question: Which model did you use to train your word vectors with word2vec? Skip-gram or cbow? Is this the standard model as reported in Mikolov et al. (2013) or a modified variant?
And which parameters did you use to train the model for each language? Always the default parameters in make_wordvectors.sh?

@Pzoom522
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Pzoom522 commented Feb 20, 2019

Given make_wordvectors.sh and make_wordvectors.py, it seems that @Kyubyong used the gensim implementation of word2vec. Thus, by default, I believe he chose CBOW model. see gensim doc

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