AEOLLM / app.py
陈俊杰
automatic
d6e3121
raw
history blame
2.2 kB
import streamlit as st
import pandas as pd
# CSS样式
st.markdown("""
<style>
h1 {
font-size: 2.5em; /* 标题字体大小 */
}
.stDataFrame {
font-family: Helvetica;
}
.dataframe th, .dataframe td {
width: auto;
min-width: 500px;
}
</style>
""", unsafe_allow_html=True)
# 标题
st.title('🏆AEOLLM Leaderboard')
# 描述
st.markdown("""
This leaderboard is used to show the performance of the **automatic evaluation methods of LLMs** submitted by the **AEOLLM team** on four tasks:
- Summary Generation (SG)
- Non-Factoid QA (NFQA)
- Dialogue Generation (DG)
- Text Expansion (TE).
Details of AEOLLLM can be found at the link: [https://cjj826.github.io/AEOLLM/](https://cjj826.github.io/AEOLLM/)
""", unsafe_allow_html=True)
# 创建示例数据
SG = {
"methods": ["Model A", "Model B", "Model C"],
"team": ["U1", "U2", "U3"],
"acc": [0.75, 0.64, 0.83],
"tau": [0.05, 0.28, 0.16],
"s": [0.12, 0.27, 0.18],
}
df1 = pd.DataFrame(SG)
NFQA = {
"methods": ["Model A", "Model B", "Model C"],
"team": ["U1", "U2", "U3"],
"acc": [0.75, 0.64, 0.83],
"tau": [0.05, 0.28, 0.16],
"s": [0.12, 0.27, 0.18]
}
df2 = pd.DataFrame(NFQA)
DG = {
"methods": ["Model A", "Model B", "Model C"],
"team": ["U1", "U2", "U3"],
"acc": [0.75, 0.64, 0.83],
"tau": [0.05, 0.28, 0.16],
"s": [0.12, 0.27, 0.18]
}
df3 = pd.DataFrame(DG)
TE = {
"methods": ["Model A", "Model B", "Model C"],
"team": ["U1", "U2", "U3"],
"acc": [0.75, 0.64, 0.83],
"tau": [0.05, 0.28, 0.16],
"s": [0.12, 0.27, 0.18]
}
df4 = pd.DataFrame(TE)
# 创建标签页
tab1, tab2, tab3, tab4 = st.tabs(["SG", "NFQA", "DG", "TE"])
# 在标签页 1 中添加内容
with tab1:
st.header("Summary Generation")
st.dataframe(df1, use_container_width=True)
# 在标签页 2 中添加内容
with tab2:
st.header("Non-Factoid QA")
st.dataframe(df2, use_container_width=True)
# 在标签页 3 中添加内容
with tab3:
st.header("Dialogue Generation")
st.dataframe(df3, use_container_width=True)
# 在标签页 4 中添加内容
with tab4:
st.header("Text Expansion")
st.dataframe(df4, use_container_width=True, )