Word2vec in Pytorch

This repo has learnt a lot from this repo

This repo implements the SkipGram model with negative sampling of Word2vec by Mikolov.

Tricks below are also implemented:

• subsampling
• negative sampling with pow weight decay
• learning rate decay

Requirements

• PyTorch >= 0.4.1
• Gensim >= 3.6.0 (for testing only)

Fast run

To quickly run the train model, just run

python train.py

which uses a Chinese corpus to train the Word2vec model. There is another toy corpus in English you can use located in data/trainset.txt, which is actually a "Jane Eyre" novel.

Issues and PRs are welcomed!

Reference

[1] Mikolov T, Sutskever I, Chen K, et al. Distributed representations of words and phrases and their compositionality[C]//Advances in neural information processing systems. 2013: 3111-3119.