Remove column for average

src/display/utils.py

@@ -26,7 +26,7 @@ auto_eval_column_dict = []
 # auto_eval_column_dict.append(["model_type_symbol", ColumnContent, ColumnContent("T", "str", True, never_hidden=True)])
 auto_eval_column_dict.append(["model", ColumnContent, ColumnContent("Model", "markdown", True, never_hidden=True)])
 #Scores
-auto_eval_column_dict.append(["average", ColumnContent, ColumnContent("Average ⬆️", "markdown", True)])
+# auto_eval_column_dict.append(["average", ColumnContent, ColumnContent("Average ⬆️", "markdown", True)])
 for task in Tasks:
     auto_eval_column_dict.append([task.name, ColumnContent, ColumnContent(task.value.col_name, "markdown", True)])
 # # Model information

src/leaderboard/read_evals.py

@@ -109,7 +109,7 @@ class EvalResult:
 
     def to_dict(self):
         """Converts the Eval Result to a dict compatible with our dataframe display"""
-        average = sum([v for v in self.results.values() if v is not None]) / len(Tasks)
+        # average = sum([v for v in self.results.values() if v is not None]) / len(Tasks)
         data_dict = {
             "eval_name": self.eval_name,  # not a column, just a save name,
             # AutoEvalColumn.precision.name: self.precision.value.name,
@@ -119,7 +119,7 @@ class EvalResult:
             # AutoEvalColumn.architecture.name: self.architecture,
             AutoEvalColumn.model.name: make_clickable_model(self.full_model),
             # AutoEvalColumn.revision.name: self.revision,
-            AutoEvalColumn.average.name: average,
+            # AutoEvalColumn.average.name: average,
             AutoEvalColumn.license.name: self.license,
             # AutoEvalColumn.likes.name: self.likes,
             # AutoEvalColumn.params.name: self.num_params,

src/populate.py

@@ -38,7 +38,7 @@ def get_leaderboard_df(results_path: str, requests_path: str, cols: list, benchm
 
     df = pd.DataFrame.from_records(all_data_json)
 
-    df = df.sort_values(by=[AutoEvalColumn.average.name], ascending=False)
+    # df = df.sort_values(by=[AutoEvalColumn.average.name], ascending=False)
     df = df[cols].round(decimals=2)
 
     # TMP: Debug