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MiniWord2Vec

This application is an implementation of both the skipgram and cbow techniques used in the Word2Vec algorithm.

Requirements

Support for Python 2 and 3. Install the package requirements via

pip install -r requirements.txt

Note

Requires cupy to run on GPU for fast computations, and that is the default behaviour. cupy requires CUDA related libraries, cuDNN and NCCL, to be installed before installing CuPy.

Replace import cupy as np with import numpy as np if you wish to run it on the CPU.

Data

The training data can be found in the data/ folder.

Usage

For training, use the run script. For CBoW, use:

./run cbow

For Skipgram, use:

./run skipgram

Tuning Parameters

You can edit the parameters by specifying their values in the run file. Parameters that can be edited:

  • Dimension of the word embedding, default: 300
  • No. of epochs to train the data on, default: 100
  • Window size for CBoW, default: 3

Output

Currently stores the outputs in the form of .npy files after each epoch in the utils/ folder.