fixed update

refresh.py

@@ -323,11 +323,17 @@ def get_mteb_data(tasks=["Clustering"], langs=[], datasets=[], fillna=True, add_
  df['MLSUMClusteringS2S (fr)'] = df['MLSUMClusteringS2S (fr)'].fillna(df['MLSUMClusteringS2S'])
  datasets.remove('MLSUMClusteringS2S')
  if ('PawsXPairClassification (fr)' in datasets) and ('PawsX (fr)' in cols):
- if 'PawsXPairClassification (fr)' in cols:
- df['PawsXPairClassification (fr)'] = df['PawsXPairClassification (fr)'].fillna(df['PawsX (fr)'])
- else:
+ # for the first bit no model has it, hence no column for it. We can remove this in a month or so
+ if "PawsXPairClassification (fr)" not in cols:
  df['PawsXPairClassification (fr)'] = df['PawsX (fr)']
+ else:
+ df['PawsXPairClassification (fr)'] = df['PawsXPairClassification (fr)'].fillna(df['PawsX (fr)'])
+ # make all the columns the same
  datasets.remove('PawsX (fr)')
+ cols.remove('PawsX (fr)')
+ df.drop(columns=['PawsX (fr)'], inplace=True)
+ cols.append('PawsXPairClassification (fr)')
+ 
  # Filter invalid columns
  cols = [col for col in cols if col in base_columns + datasets]
  i = 0
@@ -356,10 +362,7 @@ def get_mteb_average(task_dict: dict):
  )
  # Debugging:
  # DATA_OVERALL.to_csv("overall.csv")
- try:
- DATA_OVERALL.insert(1, f"Average ({len(all_tasks)} datasets)", DATA_OVERALL[all_tasks].mean(axis=1, skipna=False))
- except Exception as e:
- breakpoint()
+ DATA_OVERALL.insert(1, f"Average ({len(all_tasks)} datasets)", DATA_OVERALL[all_tasks].mean(axis=1, skipna=False))
  for i, (task_category, task_category_list) in enumerate(task_dict.items()):
  DATA_OVERALL.insert(i+2, f"{task_category} Average ({len(task_category_list)} datasets)", DATA_OVERALL[task_category_list].mean(axis=1, skipna=False))
  DATA_OVERALL.sort_values(f"Average ({len(all_tasks)} datasets)", ascending=False, inplace=True)