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I have trained a word2vec model using GenSim 4.

The problem is that my corpus is quite small.

How can I test the quality of the word embeddings I have obtained?

Is there some standard measures to do that?

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  • $\begingroup$ Theoretically, a w2v model is a NN model. I think you can evaluate it as the other machine learning models. $\endgroup$
    – heroEM
    Dec 3, 2020 at 2:49

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One way to test your embedding is see how often your model agrees with the common consensus of how other embeddings complete word analogies. A collection of established word embedding analogies are here.

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