Creating train,test data for Word2Vec model
Word2Vec is considered an 'unsupervised' algorithm, so at least during its training, it is not typical to hold back any 'test' data for later evaluation. 
A Word2Vec model is usually then evaluated on how well it helps some other process - such as the analogy-solving highlighted by the original paper. In gensim, the method [evaluate_word_analogies()][1] can repeat that process. But note: word-vectors that perform best on word-analogies my not be best for other purposes, like classification or info-retrieval. It's always best to evaluate & tune your word-vectors in a repeatable way that's related to your actual underlying use. 
(If you're using the Word2Vec model's outputs - word-vectors specific to your domain – as part of a larger system, where some steps should be evaluated with held-back data, the decision of whether to train the Word2Vec component on all data could go either way, depending on other considerations.)
I am trying to create a W2V model and then generate train and test data to be used for my model.My question is how can I generate test data after I am done with creating a W2V model with my train data.