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Update app.py

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  1. app.py +15 -1
app.py CHANGED
@@ -171,7 +171,21 @@ with tab1:
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  # st.markdown('<div class="title">Leaderboard</div>', unsafe_allow_html=True)
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  st.markdown('<div class="tab-content">', unsafe_allow_html=True)
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- st.markdown('# Metric Explanation')
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  st.markdown('@Farima populate here')
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  st.markdown("""
 
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  # st.markdown('<div class="title">Leaderboard</div>', unsafe_allow_html=True)
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  st.markdown('<div class="tab-content">', unsafe_allow_html=True)
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+ st.markdown('Metrics Explanation')
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+ st.markdown( '''
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+ <div class="metric">
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+ <br/>
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+ <p style="font-size:16px;">
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+ <strong> Factual Precision </strong> measures the ratio of supported units divided by all units averaged over model responses. <strong> Hallucination Score </strong> measures the degree of incorrect or inconclusive content units in model response, with details provided in the paper. We also provide statistics on the average number of unsupported unit (<strong>Avg. Unsupported</strong>), average number of units labelled as undecided (<strong>Avg. Undecided</strong>), Average length of response in terms of the number of tokens, and the average verifiable units existing in the model responses.
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+ </p>
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+ <p style="font-size:16px;">
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+ πŸ”’ for closed LLMs; πŸ”‘ for open-weights LLMs; 🚨 for newly added models"
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+ </p>
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+ </div>
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+ ''',
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+ unsafe_allow_html=True
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+ )
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+
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  st.markdown('@Farima populate here')
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  st.markdown("""