Catching exceptions in processing files. As new data is introduced, I want to know which files may have different formats and cause problems, but the application shouldn't halt if it can't process a single file

Returning just a single file per model directory. Manually removing gpt-j-6b for now because there is something that is causing problems with processing the data

removing models that are known to have training data contaminated with evaluations

Fixed type error

WIP commit. Currently have nlargest error

Added organization to dataframe

removed code to print the number of outliers. could add it back later as logging potentially

MC1 column had 8 rows with a value of 1. It didn't make sense given the next highest value was 0.47 . Assuming they were data errors, they were removed

truthfulqa data added to dataframe

Refactor to make later code changes easier

Added test for removal of undesired columns. fixed code error in column removal

Moved rank data into a separate method and dataframe

Extracting parameter data from the names of the models

Refactor. Extracted methods.

Refactoring. Moved ResultDataProcessor class to a separate file to make it easier to use with experimentation in a jupyter notebook