use only CV and compute dist from avrg. WER and CV WER.

app.py

@@ -12,15 +12,9 @@ column_names = {
     "MODEL": "Model",
     "Avg. WER": "Average WER ⬇️",    
     "RTF": "RTF (1e-3) ⬇️",
-    "AMI WER": "AMI",
-    "Earnings22 WER": "Earnings22",
-    "Gigaspeech WER": "Gigaspeech",
-    "LS Clean WER": "LS Clean",
-    "LS Other WER": "LS Other",
-    "SPGISpeech WER": "SPGISpeech",
-    "Tedlium WER": "Tedlium",
-    "Voxpopuli WER": "Voxpopuli",
-    "Common Voice WER": "Common Voice"}
+    "Common Voice WER": "Common Voice",
+    "D_AVG_CV_WER": "Delta AVG-CV WER",
+}
 
 eval_queue_repo, requested_models, csv_results = load_all_info_from_dataset_hub()
 
@@ -42,7 +36,10 @@ for col in original_df.columns:
         original_df[col] = original_df[col].apply(formatter) # For numerical values
  
 original_df.rename(columns=column_names, inplace=True)
-original_df.sort_values(by='Average WER ⬇️', inplace=True)
+original_df.sort_values(by='Common Voice WER', inplace=True)
+
+# Compute delta between average WER and CV WER
+original_df['Var. AVG-CV WER'] = original_df['Average WER ⬇️'] - original_df['Common Voice']
 
 COLS = [c.name for c in fields(AutoEvalColumn)]
 TYPES = [c.type for c in fields(AutoEvalColumn)]