formatter
Browse files- app.py +4 -2
- src/leaderboard/read_evals.py +1 -1
app.py
CHANGED
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@@ -63,12 +63,14 @@ def init_leaderboard(dataframe):
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#if dataframe is None or dataframe.empty:
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#raise ValueError("Leaderboard DataFrame is empty or None.")
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dataframe = dataframe[[c.name for c in fields(AutoEvalColumn) if c.displayed_by_default]]
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-
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lambda rows: [
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"background-color: red;color:white" if (value >0) else "background-color: green;color:white" for value in rows
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],
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subset=["Contamination Score"],
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)
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return gr.Dataframe(
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value=styler,
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#if dataframe is None or dataframe.empty:
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#raise ValueError("Leaderboard DataFrame is empty or None.")
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dataframe = dataframe[[c.name for c in fields(AutoEvalColumn) if c.displayed_by_default]]
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+
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+
styler = dataframe.style.format({'Contamination Score': "{:.2f}",'Benchmark Score': "{:.2f}",'Speed (words/sec)': "{:.2f}"}).apply(
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lambda rows: [
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"background-color: red;color:white !important" if (value >0) else "background-color: green;color:white !important" for value in rows
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],
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subset=["Contamination Score"],
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)
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+
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return gr.Dataframe(
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value=styler,
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src/leaderboard/read_evals.py
CHANGED
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@@ -138,7 +138,7 @@ class EvalResult:
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dimension_name = eval_dim.value.col_name
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dimension_value = self.results[eval_dim.value.metric]
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if dimension_name == "Contamination Score":
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-
dimension_value =
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data_dict[dimension_name] = dimension_value
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return data_dict
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dimension_name = eval_dim.value.col_name
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dimension_value = self.results[eval_dim.value.metric]
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if dimension_name == "Contamination Score":
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+
dimension_value = 0 if dimension_value < 0 else round(dimension_value,2)
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data_dict[dimension_name] = dimension_value
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return data_dict
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