cjj: teamId

app.py

@@ -32,9 +32,10 @@ Details of AEOLLLM can be found at the link: [https://aeollm.github.io/](https:/
 """, unsafe_allow_html=True)
 # 创建示例数据
 
+# teamId 唯一标识码
 DG = {
+    "teamId": ["baseline1", "baseline2", "baseline3", "baseline4"],
     "methods": ["chatglm3-6b", "baichuan2-13b", "chatglm-pro", "gpt-4o-mini"],
-    "team": ["baseline", "baseline", "baseline", "baseline"],
     "accuracy": [0.5806, 0.5483, 0.6001, 0.6472],
     "kendall's tau": [0.3243, 0.1739, 0.3042, 0.4167],
     "spearman": [0.3505, 0.1857, 0.3264, 0.4512]
@@ -45,8 +46,8 @@ for col in df1.select_dtypes(include=['float64', 'int64']).columns:
     df1[col] = df1[col].apply(lambda x: f"{x:.4f}")
 
 TE = {
+    "teamId": ["baseline1", "baseline2", "baseline3", "baseline4"],
     "methods": ["chatglm3-6b", "baichuan2-13b", "chatglm-pro", "gpt-4o-mini"],
-    "team": ["baseline", "baseline", "baseline", "baseline"],
     "accuracy": [0.5107, 0.5050, 0.5461, 0.5581],
     "kendall's tau": [0.1281, 0.0635, 0.2716, 0.3864],
     "spearman": [0.1352, 0.0667, 0.2867, 0.4157]
@@ -56,8 +57,8 @@ for col in df2.select_dtypes(include=['float64', 'int64']).columns:
     df2[col] = df2[col].apply(lambda x: f"{x:.4f}")
 
 SG = {
+    "teamId": ["baseline1", "baseline2", "baseline3", "baseline4"],
     "methods": ["chatglm3-6b", "baichuan2-13b", "chatglm-pro", "gpt-4o-mini"],
-    "team": ["baseline", "baseline", "baseline", "baseline"],
     "accuracy": [0.6504, 0.6014, 0.7162, 0.7441],
     "kendall's tau": [0.3957, 0.2688, 0.5092, 0.5001],
     "spearman": [0.4188, 0.2817, 0.5403, 0.5405],
@@ -67,8 +68,8 @@ for col in df3.select_dtypes(include=['float64', 'int64']).columns:
     df3[col] = df3[col].apply(lambda x: f"{x:.4f}")
 
 NFQA = {
+    "teamId": ["baseline1", "baseline2", "baseline3", "baseline4"],
     "methods": ["chatglm3-6b", "baichuan2-13b", "chatglm-pro", "gpt-4o-mini"],
-    "team": ["baseline", "baseline", "baseline", "baseline"], 
     "accuracy": [0.5935, 0.5817, 0.7000, 0.7203],
     "kendall's tau": [0.2332, 0.2389, 0.4440, 0.4235],
     "spearman": [0.2443, 0.2492, 0.4630, 0.4511]
@@ -80,12 +81,10 @@ for col in df4.select_dtypes(include=['float64', 'int64']).columns:
 # 创建标签页
 tab1, tab2, tab3, tab4 = st.tabs(["DG", "TE", "SG", "NFQA"])
 
-# 在标签页 3 中添加内容
 with tab1:
     st.markdown("""Task: Dialogue Generation; Dataset: DialyDialog""", unsafe_allow_html=True)
     st.dataframe(df1, use_container_width=True)
 
-# 在标签页 4 中添加内容
 with tab2:
     st.markdown("""Task: Text Expansion; Dataset: WritingPrompts""", unsafe_allow_html=True)
     st.dataframe(df2, use_container_width=True)
@@ -94,7 +93,6 @@ with tab3:
     st.markdown("""Task: Summary Generation; Dataset: Xsum""", unsafe_allow_html=True)
     st.dataframe(df3, use_container_width=True)
 
-# 在标签页 2 中添加内容
 with tab4:
     st.markdown("""Task: Non-Factoid QA; Dataset: NF_CATS""", unsafe_allow_html=True)
     st.dataframe(df4, use_container_width=True)