This is a repo for training a word2vec model on domain specific data (here chemistry and material science).
First, you shoud install all the required libraries.
pip install -r requirements.txt
The goal is to learn a sophisticated word embedding for domain specific data. Also, I have used Optuna for hyperparameter tuning. So, It autimaticall searches in the possible space and find the best hyperparameters for embedding.
Generally, There are three specific parts in this repo:
- Preprocessing data (to transform the data to the appropriate format for gensim)
- Word embedding from scratch
- Funetuning pre-existing model.
You can learn more about how to run (and reproduce the results) by going through run.ipynb.
Please let me know if you have any questions