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Change the way the parsable questions are expressed from numerical to percentage
#1
by
Draedon
- opened
app.py
CHANGED
@@ -18,6 +18,8 @@ with demo:
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gr.HTML(TITLE)
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gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
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# load dataframe from csv
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# leaderboard_df = pd.read_csv("benchmark_results.csv")
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leaderboard_df = []
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@@ -54,6 +56,10 @@ with demo:
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leaderboard_df["Num Questions Parseable"] = leaderboard_df[["Num Questions Parseable", "Error"]].apply(
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lambda x: parse_parseable(x), axis=1)
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def get_params(model_name):
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if model_name in metadata:
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@@ -82,8 +88,9 @@ with demo:
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leaderboard_df = leaderboard_df.sort_values(by=["Benchmark Score", "Num Questions Parseable"],
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ascending=[False, False])
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# rename
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leaderboard_df = leaderboard_df.rename(columns={"Model Path": "Model"})
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leaderboard_df_styled = leaderboard_df.style.background_gradient(cmap="RdYlGn")
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leaderboard_df_styled = leaderboard_df_styled.background_gradient(cmap="RdYlGn_r", subset=['Params'])
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@@ -92,7 +99,7 @@ with demo:
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# for col in ["Benchmark Score", "Num Questions Parseable"]:
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rounding["Benchmark Score"] = "{:.2f}"
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-
rounding["
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rounding["Params"] = "{:.0f}"
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leaderboard_df_styled = leaderboard_df_styled.format(rounding)
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gr.HTML(TITLE)
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gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
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NUMBER_OF_QUESTIONS = 171.0
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# load dataframe from csv
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# leaderboard_df = pd.read_csv("benchmark_results.csv")
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leaderboard_df = []
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leaderboard_df["Num Questions Parseable"] = leaderboard_df[["Num Questions Parseable", "Error"]].apply(
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lambda x: parse_parseable(x), axis=1)
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def fraction_to_percentage(numerator: float, denominator: float) -> float:
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return (numerator / denominator) * 100
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leaderboard_df["Num Questions Parseable"] = leaderboard_df["Num Questions Parseable"].apply(lambda x: fraction_to_percentage(float(x), NUMBER_OF_QUESTIONS))
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def get_params(model_name):
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if model_name in metadata:
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leaderboard_df = leaderboard_df.sort_values(by=["Benchmark Score", "Num Questions Parseable"],
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ascending=[False, False])
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# rename columns
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leaderboard_df = leaderboard_df.rename(columns={"Model Path": "Model"})
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leaderboard_df = leaderboard_df.rename(columns={"Num Questions Parseable": "Percentage Questions Parseable"})
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leaderboard_df_styled = leaderboard_df.style.background_gradient(cmap="RdYlGn")
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leaderboard_df_styled = leaderboard_df_styled.background_gradient(cmap="RdYlGn_r", subset=['Params'])
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# for col in ["Benchmark Score", "Num Questions Parseable"]:
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rounding["Benchmark Score"] = "{:.2f}"
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rounding["Percentage Questions Parseable"] = "{:.2f}"
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rounding["Params"] = "{:.0f}"
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leaderboard_df_styled = leaderboard_df_styled.format(rounding)
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