[Add] average to df

app.py

@@ -10,7 +10,7 @@ import json
 import requests
 
 from envs import API, EVAL_REQUESTS_PATH, TOKEN, QUEUE_REPO
-from utils import LLM_BENCHMARKS_ABOUT_TEXT, LLM_BENCHMARKS_SUBMIT_TEXT, custom_css, jsonl_to_dataframe, add_average_row_to_df
+from utils import LLM_BENCHMARKS_ABOUT_TEXT, LLM_BENCHMARKS_SUBMIT_TEXT, custom_css, jsonl_to_dataframe
 
 
 
@@ -108,8 +108,8 @@ base_df = jsonl_to_dataframe(str(abs_path / "leaderboard_base.jsonl"))
 all_columns = ["Average ⬆️", "Precision", "#Params (B)", "Part Multiple Choice", "ARC Easy", "ARC Challenging", "MMLU Pro", "GSM8k Persian", "Multiple Choice Persian"]
 columns_to_average = ["Part Multiple Choice", "ARC Easy", "ARC Challenging", "MMLU Pro", "GSM8k Persian", "Multiple Choice Persian"]
 
-persian_df = add_average_row_to_df(persian_df, columns_to_average)
-base_df = add_average_row_to_df(base_df, columns_to_average)
+persian_df["Average ⬆️"] = persian_df[columns_to_average].mean(axis=1)
+base_df["Average ⬆️"] = base_df[columns_to_average].mean(axis=1)
 
 
 with gr.Blocks(css=custom_css) as demo:

utils.py

@@ -149,16 +149,3 @@ def load_jsonl(input_file):
 def jsonl_to_dataframe(input_file):
     data = load_jsonl(input_file)
     return pd.DataFrame(data)
-
-
-def compute_averages(df, columns_to_average):
-    average_metrics = {col: df[col].mean() for col in columns_to_average if col in df}
-    average_metrics["Model"] = "Average ⬆️"  # Label the row as "Average"
-    return average_metrics
-
-def add_average_row_to_df(df, columns_to_average):
-    average_row = compute_averages(df, columns_to_average)
-    average_df = pd.DataFrame([average_row])
-    print(average_df.columns, average_df)
-    df = pd.concat([df, average_df], ignore_index=True)
-    return df