Project File Structure

The file structure of the project is the following:

• src: directory containing the source code necessary to execute the project
• notebooks: a folder containing the notebooks used to deploy the project to google colab
• data: a folder containing all the data needed to run the project and also the one's produced during runs
• configs: a folder containing the configs used to pass all the appropriate parameters to the program
• runs: a folder containing the output produced by the transformer experiments excecuted

Executing Project

In order to execute the project's code one has to follow the steps below:

• Create a conda environment by using the following installation commands:

  • conda create --name cil python=3.9
  • conda install numpy
  • conda install pandas
  • conda install tqdm
  • conda install nltk
  • conda install yacs
  • conda install jsonlines
  • conda install -c anaconda scikit-learn
  • conda install -c anaconda gensim=4.1.2
  • conda install -c conda-forge xgboost
  • conda install -c conda-forge keras
  • conda install -c conda-forge tensorflow
  • conda install -c conda-forge transformers
  • pip install accelerate
  • pip install fasttext
  • pip install ekphrasis -U
  • pip install nlp_dedup

  Although providing a unified file that would be able to recreate our environment that ability was hindered by the lack of conda support for various packages as shown above

• Download and place the data provided for the project in the data/ folder

• Download the additional data from https://www.kaggle.com/datasets/kazanova/sentiment140 and place them in the data/additional/ folder

• Download the GloVe tweet embeddings (glove.twitter.27B.zip) from https://nlp.stanford.edu/projects/glove/ and place them in the data/additional/ folder

• Specify the config setups you wish to execute

• Navigate to src/__init__.py and decide if a baseline or a novelty run is being performed

• Execute the main function found in src/__init__.py, either from terminal or an IDE software.