update:1220

app.py

@@ -265,43 +265,43 @@ elif page == "LeaderBoard":
         "Spearman (Non-Factoid QA)": [],
     }
 
-    TeamId = ["baseline", "baseline", "baseline", "baseline", 'ISLab', 'ISLab', 'ISLab', 'ISLab', 'ISLab', 'ISLab', 'ISLab', 'ISLab', 'ISLab', "ISLab"]
-    Methods = ["chatglm3-6b", "baichuan2-13b", "chatglm-pro", "gpt-4o", 'gpt4o-mini-baseline', 'gpt4o-mini-baseline2', 'llama3-1-baseline', 'llama3-1-baseline2', 'short -test', 'lst2', 'lst3', 'lstt', "llama3-1_baseline3", "llama3-1_baseline4"]
+    TeamId = ["baseline", "baseline", "baseline", "baseline", 'ISLab', 'ISLab', 'ISLab', 'ISLab', 'default5_llm']
+    Methods = ["chatglm3-6b", "baichuan2-13b", "chatglm-pro", "gpt-4o", "llama3-1_baseline5", "llama3-1_baseline6", "llama3-1-baseline7", "llama3-2-baseline", "梅朗"]
 
     # teamId 唯一标识码
     DG = {
         "TeamId": TeamId,
         "Methods": Methods,
-        "Accuracy": [0.5806, 0.5483, 0.6001, 0.6472, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
-        "Kendall's Tau": [0.3243, 0.1739, 0.3042, 0.4167, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
-        "Spearman": [0.3505, 0.1857, 0.3264, 0.4512, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
+        "Accuracy": [0.5806, 0.5483, 0.6001, 0.6472, 0, 0, 0, 0, 0.6504481792717087],
+        "Kendall's Tau": [0.3243, 0.1739, 0.3042, 0.4167, 0, 0, 0, 0, 0.4034134076281578],
+        "Spearman": [0.3505, 0.1857, 0.3264, 0.4512, 0, 0, 0, 0, 0.4303514807222638],
     }
     df1 = pd.DataFrame(DG)
 
     TE = {
         "TeamId": TeamId,
         "Methods": Methods,
-        "Accuracy": [0.5107, 0.5050, 0.5461, 0.5581, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
-        "Kendall's Tau": [0.1281, 0.0635, 0.2716, 0.3864, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
-        "Spearman": [0.1352, 0.0667, 0.2867, 0.4157, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
+        "Accuracy": [0.5107, 0.5050, 0.5461, 0.5581, 0.5067545088210725, 0.4766805549971185, 0, 0, 0.511188817632316],
+        "Kendall's Tau": [0.1281, 0.0635, 0.2716, 0.3864, 0.18884532500063825, 0.31629653258509166, 0, 0, 0.10828008098753536],
+        "Spearman": [0.1352, 0.0667, 0.2867, 0.4157, 0.2033137543983765, 0.35189638758373964, 0, 0, 0, 0.11421806788123415],
     }
     df2 = pd.DataFrame(TE)
 
     SG = {
         "TeamId": TeamId,
         "Methods": Methods,
-        "Accuracy": [0.6504, 0.6014, 0.7162, 0.7441, 0.7684735750360749, 0.7659274997877937, 0.7702904570919278, 0.7707237554112554, 0.7171193287921227, 0.7433948731007554, 0.7669608108394873, 0.7428272483235718, 0.72930255814447, 0.785859169425346],
-        "Kendall's Tau": [0.3957, 0.2688, 0.5092, 0.5001, 0.5139446977332496, 0.5635917219315821, 0.5789961063044075, 0.5704551232357526, 0.5678532047471645, 0.49448829251394394, 0.5329295390524793, 0.5740499751693215, 0.5010345926703657, 0.5965020344411163],
-        "Spearman": [0.4188, 0.2817, 0.5403, 0.5405, 0.5610788011671747, 0.6164421350125108, 0.6242002118163157, 0.6148419886082258, 0.6019919123404138, 0.533764470447043, 0.5685534007297164, 0.6145790156923595, 0.5415557641332287, 0.6416245134903308],
+        "Accuracy": [0.6504, 0.6014, 0.7162, 0.7441, 0.7518953983108395, 0.7870818213649097, 0.6187623875307698, 0.8003185213479332, 0.7007955341227401],
+        "Kendall's Tau": [0.3957, 0.2688, 0.5092, 0.5001, 0.5377072309689559, 0.5709963447418871, 0.30897221697376714, 0.6064826537169805, 0.4819411311747811],
+        "Spearman": [0.4188, 0.2817, 0.5403, 0.5405, 0.5830423197486431, 0.6276373633425562, 0.324348752437819, 0.6664032039425867, 0.5076789062134682],
     }
     df3 = pd.DataFrame(SG)
 
     NFQA = {
         "TeamId": TeamId,
         "Methods": Methods,
-        "Accuracy": [0.5935, 0.5817, 0.7000, 0.7203, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
-        "Kendall's Tau": [0.2332, 0.2389, 0.4440, 0.4235, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
-        "Spearman": [0.2443, 0.2492, 0.4630, 0.4511, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
+        "Accuracy": [0.5935, 0.5817, 0.7000, 0.7203, 0, 0, 0, 0, 0.5922294372294372],
+        "Kendall's Tau": [0.2332, 0.2389, 0.4440, 0.4235, 0, 0, 0, 0, 0.1701874070113157],
+        "Spearman": [0.2443, 0.2492, 0.4630, 0.4511, 0, 0, 0, 0, 0.18058287732894646],
     }
     df4 = pd.DataFrame(NFQA)