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import pandas as pd
import os
import fnmatch
import json
class ResultDataProcessor:
def __init__(self, directory='results', pattern='results*.json'):
self.directory = directory
self.pattern = pattern
self.data = self.process_data()
@staticmethod
def _find_files(directory, pattern):
for root, dirs, files in os.walk(directory):
for basename in files:
if fnmatch.fnmatch(basename, pattern):
filename = os.path.join(root, basename)
yield filename
def _read_and_transform_data(self, filename):
with open(filename) as f:
data = json.load(f)
df = pd.DataFrame(data['results']).T
return df
def _cleanup_dataframe(self, df, model_name):
df = df.rename(columns={'acc': model_name})
df.index = (df.index.str.replace('hendrycksTest-', 'MMLU_', regex=True)
.str.replace('harness\|', '', regex=True)
.str.replace('\|5', '', regex=True))
return df[[model_name]]
def process_data(self):
dataframes = [self._cleanup_dataframe(self._read_and_transform_data(filename), filename.split('/')[2])
for filename in self._find_files(self.directory, self.pattern)]
data = pd.concat(dataframes, axis=1).transpose()
# Add Model Name and rearrange columns
data['Model Name'] = data.index
cols = data.columns.tolist()
cols = cols[-1:] + cols[:-1]
data = data[cols]
# Remove the 'Model Name' column
data = data.drop(columns=['Model Name'])
# Add average column
data['MMLU_average'] = data.filter(regex='MMLU').mean(axis=1)
# Reorder columns to move 'MMLU_average' to the third position
cols = data.columns.tolist()
cols = cols[:2] + cols[-1:] + cols[2:-1]
data = data[cols]
# Drop specific columns
return data.drop(columns=['all', 'truthfulqa:mc|0'])
def get_data(self, selected_models):
return self.data[self.data.index.isin(selected_models)]
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