ExplainaBoard-experiments

for keeping track of experiments done with ExplanaBoard

Summary of scripts

• src/process_wmt21reports.py: organize the json reports from explainaboard into data points with metrics, also calculated URIEL distances
• src/process_wmt21train.py: organize the training data from WMT21 into data points with data size, type token ratio, ttr distance, and subword tokenization (subword not implemented yet).
• src/linear_regression.py: helper functions for linear regression.
  • builds regression pipelines from polynomial or simple regression, (basis expansion can be added too, but not added yet.)
  • trains pipelines using bootstrapping,
  • get feature importances
  • prints results (MSE and R2).
• src/generate_reports.sh : generates reports from explainaboard from a given input directory
• sample_data: for now, I have a pkl of a data frame to be used for regression related models.
• notebooks/linear-regression-analysis.ipynb: notebook containing results/plots/analysis so far, related to regression models. mostly linear regression was explored, but I tried out SVM and GPR as non-linear examples.