Add application files

app.py

@@ -9,6 +9,25 @@ leaderboard_df = pd.read_csv('leaderboard.csv').transpose()
 TITLE = "Leaderboard"
 INTRODUCTION_TEXT = "This is the leaderboard."
 
+COLS = [
+    ("Model", "str"),
+    ("FPB-acc", "number"),
+    ("FPB-F1", "number"),
+    ("FiQA-SA-F1", "number"),
+    ("Headline-AvgF1", "number"),
+    ("NER-EntityF1", "number"),
+    ("FinQA-EmAcc", "number"),
+    ("ConvFinQA-EmAcc", "number"),
+    ("BigData22-Acc", "number"),
+    ("BigData22-MCC", "number"),
+    ("ACL18-Acc", "number"),
+    ("ACL18-MCC", "number"),
+    ("CIKM18-Acc", "number"),
+    ("CIKM18-MCC", "number")
+]
+
+TYPES = [col_type for _, col_type in COLS]
+
 def launch_gradio():
     demo = gr.Blocks()
 
@@ -19,6 +38,8 @@ def launch_gradio():
         # Create a gradio table from pandas dataframe
         leaderboard_table = gr.components.Dataframe(
             value=leaderboard_df,
+            headers=[col_name for col_name, _ in COLS],
+            datatype=TYPES,
             max_rows=5,
             elem_id="leaderboard-table",
         )

leaderboard.csv

@@ -1,14 +1,9 @@
-Dataset,Metrics,GPT NeoX,OPT 66B,BLOOM,Chat GPT,GPT 4,Bloomberg GPT,FinMA 7B,FinMA 30B,FinMA 7B-full
-FPB,Acc,-,-,-,0.78,0.76,-,0.86,0.87,0.87
-FPB,F1,0.45,0.49,0.50,0.78,0.78,0.51,0.86,0.88,0.87
-FiQA-SA,F1,0.51,0.52,0.53,-,-,0.75,0.84,0.87,0.79
-Headline,AvgF1,0.73,0.79,0.77,0.77,0.86,0.82,0.98,0.97,0.97
-NER,EntityF1,0.61,0.57,0.56,0.77,0.83,0.61,0.75,0.62,0.69
-FinQA,EmAcc,-,-,-,0.58,0.63,-,0.06,0.11,0.04
-ConvFinQA,EmAcc,0.28,0.30,0.36,0.60,0.76,0.43,0.25,0.40,0.20
-BigData22,Acc,-,-,-,0.53,0.54,-,0.48,0.47,0.49
-BigData22,MCC,-,-,-,-0.025,0.03,-,0.04,0.04,0.01
-ACL18,Acc,-,-,-,0.50,0.52,-,0.50,0.49,0.56
-ACL18,MCC,-,-,-,0.005,0.02,-,0.00,0.00,0.10
-CIKM18,Acc,-,-,-,0.55,0.57,-,0.56,0.43,0.53
-CIKM18,MCC,-,-,-,0.01,0.02,-,-0.02,-0.05,-0.03
+GPT NeoX,NaN,0.45,0.51,0.73,0.61,NaN,0.28,NaN,NaN,NaN,NaN,NaN,NaN
+OPT 66B,NaN,0.49,0.52,0.79,0.57,NaN,0.30,NaN,NaN,NaN,NaN,NaN,NaN
+BLOOM,NaN,0.50,0.53,0.77,0.56,NaN,0.36,NaN,NaN,NaN,NaN,NaN,NaN
+Chat GPT,0.78,0.78,NaN,0.77,0.77,0.58,0.60,0.53,NaN,NaN,0.50,0.55,NaN
+GPT 4,0.76,0.78,NaN,0.86,0.83,0.63,0.76,0.54,0.03,0.52,0.02,0.57,0.01
+Bloomberg GPT,NaN,0.51,0.75,0.82,0.61,NaN,0.43,NaN,0.04,NaN,0.00,NaN,NaN
+FinMA 7B,0.86,0.86,0.84,0.98,0.75,NaN,0.25,NaN,NaN,NaN,NaN,NaN,NaN
+FinMA 30B,0.87,0.88,0.87,0.97,0.62,0.06,0.40,0.48,0.04,0.50,0.00,0.56,NaN
+FinMA 7B-full,0.87,0.87,0.79,0.97,0.69,0.11,0.20,0.47,0.01,0.49,0.10,-0.03