/GreyLiterature

Primary LanguageJupyter Notebook

GreyLiterature

Grey literature answer quality / user reputation measurement with BERT and DistilBERT.

Running Instructions:

  • --data_dir and --labels are always required.
  • Default sequence is 'TQA'. Use --sequence to change.
  • Default model is 'bert'. Use --model to change.
  • Default device is 'cpu'. Use --device to change.

To see all arguments and options:

python3 main.py --help

Example Run Command:

python3 main.py --data_dir='data/dp' --labels='sum_class' --device='cuda' --crop=0.25

⚠️ Here, --data-dir must include raw.csv that will be divided into train, dev and test sets, and stored under data/dp/TQA (since the default sequence is 'TQA').

References

Modified version of the code in https://github.com/isspek/west_iyte_plausability_news_detection