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Edit app.py
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app.py
CHANGED
@@ -107,7 +107,7 @@ for validator in validators:
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final_total_results[-1]["Average ⬆️"] = np.array([final_total_results[0]["ARC (25-shot) ⬆️"], final_total_results[0]["HellaSwag (10-shot) ⬆️"],final_total_results[0]["TruthfulQA (0-shot) ⬆️"], final_total_results[0]["MMLU (5-shot) ⬆️"]]).mean()
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df = pd.DataFrame(results_cumulative)
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df = df[df["cleaned_result"] == "N/A"].groupby("result", as_index=False).count().sort_values(by = ["id"], ascending = False).head(
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demo = gr.Blocks()
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with demo:
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@@ -116,7 +116,7 @@ with demo:
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with gr.Row():
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table_1 = gr.Dataframe(pd.DataFrame(final_total_results))
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with gr.Row():
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title = gr.Markdown(value=f"""# <p style="text-align: center;"> Analysis
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with gr.Row():
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table_2 = gr.Dataframe(df)
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# with gr.Row(visible = False):
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final_total_results[-1]["Average ⬆️"] = np.array([final_total_results[0]["ARC (25-shot) ⬆️"], final_total_results[0]["HellaSwag (10-shot) ⬆️"],final_total_results[0]["TruthfulQA (0-shot) ⬆️"], final_total_results[0]["MMLU (5-shot) ⬆️"]]).mean()
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df = pd.DataFrame(results_cumulative)
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df = df[df["cleaned_result"] == "N/A"].groupby("result", as_index=False).count().sort_values(by = ["id"], ascending = False).head(10)[["result","id"]].rename(columns={"result": "Result", "id": "ID"})
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demo = gr.Blocks()
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with demo:
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with gr.Row():
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table_1 = gr.Dataframe(pd.DataFrame(final_total_results))
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with gr.Row():
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title = gr.Markdown(value=f"""# <p style="text-align: center;"> Analysis Of Top 10 N/A Responses</p>""")
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with gr.Row():
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table_2 = gr.Dataframe(df)
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# with gr.Row(visible = False):
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