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update needlebench plot

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Mor-Li 2025-04-25 17:46:45 +08:00
parent bd17b3c984
commit 081c185b8f
1 changed files with 6 additions and 6 deletions
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opencompass/summarizers/needlebench.py
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@ -230,7 +230,7 @@ def save_results_to_plots(txt_results_save_path):
folder_path = os.path.join(plot_path, dataset_mapping_dict[dataset_abbr]) folder_path = os.path.join(plot_path, dataset_mapping_dict[dataset_abbr])
ensure_directory(folder_path) ensure_directory(folder_path)
save_path = os.path.join(folder_path, f'{model_name}.pdf') save_path = os.path.join(folder_path, f'{model_name}.png')
df = create_model_dataframe(parsed_data, model_name, dataset_abbr, parallel=parallel_flag) df = create_model_dataframe(parsed_data, model_name, dataset_abbr, parallel=parallel_flag)
@ -239,25 +239,25 @@ def save_results_to_plots(txt_results_save_path):
model_datasets_scores[dataset_abbr] = '{:.02f}'.format(score) model_datasets_scores[dataset_abbr] = '{:.02f}'.format(score)
overall_dataset_abbrs = multi_dataset_abbrs + origin_dataset_abbrs + parallel_dataset_abbrs overall_dataset_abbrs = multi_dataset_abbrs + origin_dataset_abbrs + parallel_dataset_abbrs
overall_score_pic_path = os.path.join(plot_path, f'{model_name}_overall.pdf') overall_score_pic_path = os.path.join(plot_path, f'{model_name}_overall.png')
merged_df = merge_dataframes(model_name, overall_dataset_abbrs, parsed_data) merged_df = merge_dataframes(model_name, overall_dataset_abbrs, parsed_data)
averaged_df = calculate_elementwise_average(model_name, merged_df) averaged_df = calculate_elementwise_average(model_name, merged_df)
overall_score = visualize(averaged_df, overall_score_pic_path, model_name, 'Overall Score') overall_score = visualize(averaged_df, overall_score_pic_path, model_name, 'Overall Score')
# Single-Retrieval # Single-Retrieval
single_retrieval_score_pic_path = os.path.join(plot_path, f'{model_name}_single_retrieval_overall.pdf') single_retrieval_score_pic_path = os.path.join(plot_path, f'{model_name}_single_retrieval_overall.png')
single_retrieval_merged_df = merge_dataframes(model_name, origin_dataset_abbrs, parsed_data) single_retrieval_merged_df = merge_dataframes(model_name, origin_dataset_abbrs, parsed_data)
single_retrieval_averaged_df = calculate_elementwise_average(model_name, single_retrieval_merged_df) single_retrieval_averaged_df = calculate_elementwise_average(model_name, single_retrieval_merged_df)
single_retrieval_overall_score = visualize(single_retrieval_averaged_df, single_retrieval_score_pic_path, model_name, 'Single-Retrieval Overall Score') single_retrieval_overall_score = visualize(single_retrieval_averaged_df, single_retrieval_score_pic_path, model_name, 'Single-Retrieval Overall Score')
# Multi-Retrieval # Multi-Retrieval
multi_retrieval_score_pic_path = os.path.join(plot_path, f'{model_name}_multi_retrieval_overall.pdf') multi_retrieval_score_pic_path = os.path.join(plot_path, f'{model_name}_multi_retrieval_overall.png')
multi_retrieval_merged_df = merge_dataframes(model_name, parallel_dataset_abbrs, parsed_data) multi_retrieval_merged_df = merge_dataframes(model_name, parallel_dataset_abbrs, parsed_data)
multi_retrieval_averaged_df = calculate_elementwise_average(model_name, multi_retrieval_merged_df) multi_retrieval_averaged_df = calculate_elementwise_average(model_name, multi_retrieval_merged_df)
multi_retrieval_overall_score = visualize(multi_retrieval_averaged_df, multi_retrieval_score_pic_path, model_name, 'Multi-Retrieval Overall Score') multi_retrieval_overall_score = visualize(multi_retrieval_averaged_df, multi_retrieval_score_pic_path, model_name, 'Multi-Retrieval Overall Score')
# Multi-Reasoning # Multi-Reasoning
multi_reasoning_score_pic_path = os.path.join(plot_path, f'{model_name}_multi_reasoning_overall.pdf') multi_reasoning_score_pic_path = os.path.join(plot_path, f'{model_name}_multi_reasoning_overall.png')
multi_reasoning_merged_df = merge_dataframes(model_name, multi_dataset_abbrs, parsed_data) multi_reasoning_merged_df = merge_dataframes(model_name, multi_dataset_abbrs, parsed_data)
multi_reasoning_averaged_df = calculate_elementwise_average(model_name, multi_reasoning_merged_df) multi_reasoning_averaged_df = calculate_elementwise_average(model_name, multi_reasoning_merged_df)
multi_reasoning_overall_score = visualize(multi_reasoning_averaged_df, multi_reasoning_score_pic_path, model_name, 'Multi-Reasoning Overall Score') multi_reasoning_overall_score = visualize(multi_reasoning_averaged_df, multi_reasoning_score_pic_path, model_name, 'Multi-Reasoning Overall Score')
@ -366,7 +366,7 @@ def visualize(df_raw, save_path: str,model_name: str ,dataset_type:str):
directory_path, original_filename = os.path.split(save_path) directory_path, original_filename = os.path.split(save_path)
filename_suffix = (title_name+'_'+dataset_name).replace(' ', '_') filename_suffix = (title_name+'_'+dataset_name).replace(' ', '_')
new_filename = f'{filename_suffix}.pdf' new_filename = f'{filename_suffix}.png'
new_save_path = os.path.join(directory_path, new_filename) new_save_path = os.path.join(directory_path, new_filename)