Only show the results if they exist

app.py

@@ -86,26 +86,27 @@ with tab1:
                     "F1 score": macro_avg_f1,
                 }
             )
-        results_df = pd.DataFrame(evaluation_metrics).sort_values(
-            "F1 score", ascending=False
-        )
-        results_df["Rank"] = range(1, len(results_df) + 1)
-        results_df["URL"] = [
-            f"https://huggingface.co/{row['model_name']}"
-            for row in model_predictions_rows
-        ]
-
-        results_df = results_df[
-            ["Rank", "Model Name", "Accuracy", "Recall", "Precision", "F1 score", "URL"]
-        ]
-        st.data_editor(
-            results_df,
-            column_config={
-                "URL": st.column_config.LinkColumn("URL", display_text="URL"),
-            },
-            hide_index=True,
-        )
-        st.write("Note: The metrics are macro-averaged across all dialects.")
+        if evaluation_metrics:
+            results_df = pd.DataFrame(evaluation_metrics).sort_values(
+                "F1 score", ascending=False
+            )
+            results_df["Rank"] = range(1, len(results_df) + 1)
+            results_df["URL"] = [
+                f"https://huggingface.co/{row['model_name']}"
+                for row in model_predictions_rows
+            ]
+
+            results_df = results_df[
+                ["Rank", "Model Name", "Accuracy", "Recall", "Precision", "F1 score", "URL"]
+            ]
+            st.data_editor(
+                results_df,
+                column_config={
+                    "URL": st.column_config.LinkColumn("URL"),
+                },
+                hide_index=True,
+            )
+            st.write("Note: The metrics are macro-averaged across all dialects.")
 
         with st.expander("Click for more information."):
             with open("leaderboard_info.md", "r") as f: