Convolutional Neural Networks for Sentence Classification

It is slightly simplified implementation of Yoon Kim's Convolutional Neural Networks for Sentence Classification paper in PyTorch.

Use of this code may be cited as follows:

@article{DBLP:journals/corr/Kim14f,
  author    = {Yoon Kim},
  title     = {Convolutional Neural Networks for Sentence Classification},
  journal   = {CoRR},
  volume    = {abs/1408.5882},
  year      = {2014},
  url       = {http://arxiv.org/abs/1408.5882},
  eprinttype = {arXiv},
  eprint    = {1408.5882},
  timestamp = {Mon, 13 Aug 2018 16:46:21 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/Kim14f.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Installation

To install this package, clone the repository from GitHub to a directory of your choice and install using pip:

git clone https://github.com/rafaelgreca/conv-sent-classification.git

You need to create a conva environment using conda and install the requirements:

conda create -n venv python=3.8.10
conda activate venv
pip install -r requirements.txt

How to Train

To run the code is very straight forward, you just need to do:

python3 main.py --model "rand"

All parameters available to use:

• --model: Which model you want to build ("rand", "static" or "non-static");
• --batch_size: The batch size of the training step (optional). Default: 50;
• --epochs: How many epochs you want to train the model (optional). Default: 25;
• --max_len: The maximum length of each sentence (optional). Default: 30.

License

MIT