Add charts for english drop

analysis/plot_leaderboard.py

@@ -1,6 +1,7 @@
 import argparse
 import logging
 from pathlib import Path
+from typing import Optional
 
 import pandas as pd
 import seaborn as sns
@@ -27,12 +28,32 @@ def get_args():
 def main():
     args = get_args()
     output_dir = Path(args.output_dir)
-    leaderboard_df = get_leaderboard(dataset=args.dataset, force_download=args.force_download)
+    if not output_dir.exists():
+        output_dir.mkdir(exist_ok=True, parents=True)
 
-    # Get average of non eng_Latn
-    leaderboard_df["Avg"] = leaderboard_df.drop(["eng_Latn", "Type"], axis=1).mean(axis=1, skipna=False)
-    leaderboard_df["Std"] = leaderboard_df.drop(["eng_Latn", "Type"], axis=1).std(axis=1, skipna=False)
-    leaderboard_df = leaderboard_df.sort_values(by=["Type", "Avg"], ascending=False)
+    # *** Leaderboard scores ***
+    logging.info("Plotting leaderboard scores for all models and languages")
+    leaderboard_df = get_leaderboard(dataset=args.dataset, force_download=args.force_download)
+    chat_leaderboard_df = get_leaderboard(
+        dataset=args.dataset,
+        force_download=args.force_download,
+        category="Chat",
+    )
+    chat_hard_leaderboard_df = get_leaderboard(
+        dataset=args.dataset,
+        force_download=args.force_download,
+        category="Chat Hard",
+    )
+    safety_leaderboard_df = get_leaderboard(
+        dataset=args.dataset,
+        force_download=args.force_download,
+        category="Safety",
+    )
+    reasoning_leaderboard_df = get_leaderboard(
+        dataset=args.dataset,
+        force_download=args.force_download,
+        category="Reasoning",
+    )
 
     # Save per model type
     model_types = leaderboard_df["Type"].unique().tolist()
@@ -54,10 +75,41 @@ def main():
         ax.set_xticklabels(ax.get_xticklabels(), rotation=45, ha="left", fontsize=16)
         ax.set_yticklabels(ax.get_yticklabels(), fontsize=16)
         fig.tight_layout()
-        fig.savefig(output_dir / f"leaderboard-{model_type.replace(' ', '_')}.png", dpi=120)
-
-
-def get_leaderboard(dataset: str, force_download: bool) -> "pd.DataFrame":
+        output_file = output_dir / f"leaderboard-{model_type.replace(' ', '_')}.png"
+        fig.savefig(output_file, dpi=120)
+        logging.info(f"Saved to {output_file}")
+
+    # *** English drop ***
+    eng_drop_df = pd.DataFrame(
+        {
+            "Overall": get_eng_drop(leaderboard_df)["Percentage_Change"],
+            "Chat": get_eng_drop(chat_leaderboard_df)["Percentage_Change"],
+            "Chat Hard": get_eng_drop(chat_hard_leaderboard_df)["Percentage_Change"],
+            "Safety": get_eng_drop(safety_leaderboard_df)["Percentage_Change"],
+            "Reasoning": get_eng_drop(reasoning_leaderboard_df)["Percentage_Change"],
+        }
+    )
+    # Only get top-3 and bottom-3. Put bottom 3 at the top rows
+    top_bottom_n = pd.concat([eng_drop_df.nsmallest(3, "Overall"), eng_drop_df.nlargest(3, "Overall")])
+    fig, ax = plt.subplots(figsize=(9, 4))
+    sns.heatmap(top_bottom_n, annot=True, cmap="Reds_r", fmt=".1f", annot_kws={"size": 18}, cbar=False)
+    ax.xaxis.tick_top()
+    fig.tight_layout()
+    output_file = output_dir / "eng-drop-overall.png"
+    fig.savefig(output_file, dpi=120)
+    logging.info(f"Saved to {output_file}")
+
+
+def get_eng_drop(df: pd.DataFrame) -> pd.DataFrame:
+    eng_drop_df = df[["eng_Latn", "Avg"]].rename(columns={"eng_Latn": "English", "Avg": "Multilingual_Avg"})
+    eng_drop_df["Percentage_Change"] = (
+        (eng_drop_df["Multilingual_Avg"] - eng_drop_df["English"]) / eng_drop_df["English"]
+    ) * 100
+    eng_drop_df = eng_drop_df.dropna().sort_values(by="Percentage_Change", ascending=True)
+    return eng_drop_df
+
+
+def get_leaderboard(dataset: str, force_download: bool, category: Optional[str] = None) -> "pd.DataFrame":
     dataset_dir = Path(snapshot_download(dataset, repo_type="dataset", force_download=force_download))
     lang_folders = [d for d in dataset_dir.iterdir() if d.is_dir()]
 
@@ -66,7 +118,10 @@ def get_leaderboard(dataset: str, force_download: bool) -> "pd.DataFrame":
     model_type = {}
     for lang_dir in lang_folders:
         model_scores = get_scores(lang_dir)
-        lang_scores[lang_dir.name] = {score["model"]: score["score"] for score in model_scores}
+        if category:
+            lang_scores[lang_dir.name] = {score["model"]: score["category_scores"][category] for score in model_scores}
+        else:
+            lang_scores[lang_dir.name] = {score["model"]: score["score"] for score in model_scores}
         for model in model_scores:
             model_name = model.get("model")
             if model_name not in model_type.keys():
@@ -77,6 +132,11 @@ def get_leaderboard(dataset: str, force_download: bool) -> "pd.DataFrame":
         left_index=True,
         right_index=True,
     )
+
+    # Get average but dont include eng_Latn
+    lang_scores_df["Avg"] = lang_scores_df.drop(["eng_Latn", "Type"], axis=1).mean(axis=1, skipna=False)
+    lang_scores_df["Std"] = lang_scores_df.drop(["eng_Latn", "Type"], axis=1).std(axis=1, skipna=False)
+    lang_scores_df = lang_scores_df.sort_values(by=["Type", "Avg"], ascending=False)
     return lang_scores_df