commit message

app.py

@@ -7,6 +7,17 @@ import gradio as gr
 from content import *
 from css import *
 import glob
+import pandas as pd
+
+
+# 假设 original_df 是一个 pandas DataFrame，并且 COLS 和 TYPES 是已经定义好的列名和数据类型列表。
+
+# 定义一个函数，用于格式化浮点数为保留一位小数的字符串
+def format_floats(val):
+    if val:
+        if isinstance(val, float):
+            return f"{val:.1f}"
+    return val
 
 
 
@@ -82,38 +93,46 @@ def get_leaderboard_df():
     df = list()
     results = [
         ["GPT-3.5-Turbo", 46.6, 42.2, 49.4],
-        ["MAmmoTH", 26.3, 21.3, 24.2],
-        ["WizardMath", 32.5, 23.0, 28.7],
-        ["MetaMath", 46.2, 37.0, 43.2],
-        ["QAlign", 57.2, 49.6, 0],
-        ["MathOctopus", 41.2, 39.5, 37.1],
-        ["MathOctopus-MAPO-DPO(ours)🔥", 57.4, 41.6, 50.4],
-        ["MetaMathOctopus", 53.0, 45.5, 39.2],
-        ["MetaMathOctopus-MAPO-DPO(ours) 👑", 64.7, 51.6, 52.9],
-        ["MistralMathOctopus", 59.0, 58.0, 56.8],
-        ["MistralMathOctopus-MAPO-DPO(ours) 👑", 74.6, 67.3, 70.0]
+        ["MAmmoTH 7B", 26.3, 21.3, 24.2],
+        ["WizardMath 7B", 32.5, 23.0, 28.7],
+        ["MetaMath 7B", 46.2, 37.0, 43.2],
+        ["QAlign 7B", 57.2, 49.6, None],
+        ["MathOctopus 7B", 41.2, 39.5, 37.1],
+        ["MathOctopus-MAPO-DPO 7B(ours)🔥", 57.4, 41.6, 50.4],
+        ["MetaMathOctopus 7B", 53.0, 45.5, 39.2],
+        ["MetaMathOctopus-MAPO-DPO 7B(ours) 👑", 64.7, 51.6, 52.9],
+        ["MistralMathOctopus 7B", 59.0, 58.0, 56.8],
+        ["MistralMathOctopus-MAPO-DPO 7B(ours) 👑", 74.6, 67.3, 70.0]
     ]
-    # for (pretrained, lang), perfs in performance_dict.items():
-    #     lang_name = LANG_NAME[lang]
-    #     arc_perf = perfs.get(ARC, 0.0)
-    #     hellaswag_perf = perfs.get(HELLASWAG, 0.0)
-    #     mmlu_perf = perfs.get(MMLU, 0.0)
-    #     truthfulqa_perf = perfs.get(TRUTHFULQA, 0.0)
-
-    #     if arc_perf * hellaswag_perf * mmlu_perf * truthfulqa_perf == 0:
-    #         continue
-    #     avg = round((arc_perf + hellaswag_perf + mmlu_perf + truthfulqa_perf) / 4, 1)
-    #     notes = ' '.join([pretrained, lang_name])
-    #     row = [pretrained, lang_name, lang, avg, arc_perf, hellaswag_perf, mmlu_perf, truthfulqa_perf, notes]
-    #     df.append(row)
+
     for i in results:
-        i.append("NOTE")
+        i.append(i[0])
     df = pd.DataFrame.from_records(results, columns=COLS)
     df = df.sort_values(by=[ MSVAMP_COL], ascending=False)
     df = df[COLS]
 
     return df
 
+def get_leaderboard_13Bdf():
+    df = list()
+    results = [
+        ["GPT-3.5-Turbo", 46.6, 42.2, 49.4],
+        ["MAmmoTH 13B", 38.6, 28.9, 29.5],
+        ["WizardMath 13B", 35.7, 28.3, 29.0],
+        ["MetaMath 13B", 46.2, 43.9, 43.3],
+        ["QAlign 13B", 62.6, 57.1, None],
+        ["MathOctopus 13B", 51.8, 46.0, 40.3],
+        ["MathOctopus-MAPO-DPO 13B (ours) 🔥", 60.1, 48.5, 53.8],
+        ["MetaMathOctopus 13B", 56.3, 51.4, 49.5],
+        ["MetaMathOctopus-MAPO-DPO 13B (ours) 👑", 67.0, 58.0, 59.8]
+    ]
+    for i in results:
+        i.append(i[0])
+    df = pd.DataFrame.from_records(results, columns=COLS)
+    df = df.sort_values(by=[ MSVAMP_COL], ascending=False)
+    df = df[COLS]
+
+    return df
 
 def search_table(df, query):
     filtered_df = df[df[NOTES_COL].str.contains(query, case=False)]
@@ -122,6 +141,7 @@ def search_table(df, query):
 
 
 original_df = get_leaderboard_df()
+original_13Bdf = get_leaderboard_13Bdf()
 
 demo = gr.Blocks(css=CUSTOM_CSS)
 with demo:
@@ -133,7 +153,7 @@ with demo:
         search_bar = gr.Textbox(
             placeholder="Search models and languages...", show_label=False, elem_id="search-bar"
         )
-
+        original_df = original_df.applymap(format_floats)
         leaderboard_table = gr.components.Dataframe(
             value=original_df,
             headers=COLS,
@@ -157,9 +177,9 @@ with demo:
         search_bar = gr.Textbox(
             placeholder="Search models and languages...", show_label=False, elem_id="search-bar"
         )
-
-        leaderboard_table = gr.components.Dataframe(
-            value=original_df,
+        original_13Bdf = original_13Bdf.applymap(format_floats)
+        leaderboard_table_13B = gr.components.Dataframe(
+            value=original_13Bdf,
             headers=COLS,
             datatype=TYPES,
             max_rows=5,
@@ -167,14 +187,14 @@ with demo:
         )
 
         # # Dummy leaderboard for handling the case when the user uses backspace key
-        hidden_leaderboard_table_for_search = gr.components.Dataframe(
-            value=original_df, headers=COLS, datatype=TYPES, max_rows=5, visible=False
+        hidden_leaderboard_table_for_search_13B = gr.components.Dataframe(
+            value=original_13Bdf, headers=COLS, datatype=TYPES, max_rows=5, visible=False
         )
 
         search_bar.change(
             search_table,
-            [hidden_leaderboard_table_for_search, search_bar],
-            leaderboard_table,
+            [hidden_leaderboard_table_for_search_13B, search_bar],
+            leaderboard_table_13B,
         )
 
     #gr.Markdown(CREDIT, elem_classes="markdown-text")