Datasets:
				
			
			
	
			
	
		
			
	
		
		
		Gresham
		
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docs(readme): refactor
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        README.md
    CHANGED
    
    | @@ -41,8 +41,101 @@ Github Repo: https://github.com/TreeAI-Lab/NumericBench | |
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            ### Loading Data
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            ### Data Format
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            ### Evaluation
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            # Dataset statistics
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            ### Loading Data
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            ``` python
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            from huggingface_hub import hf_hub_download
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            import pandas as pd
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            dataset_name_list = ['arithmetic_operation/context_arithmetic_operation.json', 'arithmetic_operation/arithmetic_operation.json',
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                        'mixed_number_sting/mixed_number_string_500_per_sample.json', 
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                        'num_list/num_list_500_per_sample_1000_length.json', 'num_list/num_list_500_per_sample_100_length.json', 
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                        'sequence/sequence_500_sample_100_length.json', 
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                        'stock/single-turn/stock_500_per_sample_150_length.json', 'stock/single-turn/stock_500_per_sample_300_length.json', 'stock/multi-turn/stock_multi_turn_100_per_sample_100_length.json',
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                        'weather/single-turn/weather_500_per_sample_200_length.json', 'weather/single-turn/weather_500_per_sample_400_length.json', 'weather/multi-turn/weather_multi_turn_100_per_sample_100_length.json'
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                        ]
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            REPO_ID = "TreeAILab/NumericBench"
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            for dataset_name in dataset_name_list:
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                dataset = pd.read_json(
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                    hf_hub_download(repo_id=REPO_ID, filename=dataset_name, repo_type="dataset")
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                )
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            ```
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            Alternatively, you can download the dataset from [this link](https://zenodo.org/records/14875784?token=eyJhbGciOiJIUzUxMiJ9.eyJpZCI6IjZhYjZlYzYwLWZkMTgtNGU1Ni1iM2I2LWUwNWVlMGIwZmYwZCIsImRhdGEiOnt9LCJyYW5kb20iOiIwNzQxNmU0NWY5ZDkxMzQ4ODVmYjdlZDgyOGJmNjVhYSJ9.m-_8Owb3TohJ76cGt2Mu4wrpsxMgC4E_aJG7Q07KHOTlKaxB4kipMY3eBZPaQEIkOv_iJEkRmlvZr23rLkTMBw).
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            ### Data Format
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            Due to the excessive length of the content, "..." is used to indicate omission.
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            ##### single-turn
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            ``` json
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            {
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                "system_prompt": "...",
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                "system_prompt_cot": "...",
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                "description": "...",
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                "data": [
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                    {
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                        "idx": 0,
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                        "question_index": 0,
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                        "question": "What is the result of A + B? Please round the answer to two decimal places. ",
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                        "struct_data": "{'A': 6.755, 'B': -1.225}",
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                        "answer": 5.53,
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                        "ability": "1-digit integer with 3 decimal places"
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                    },
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                            {
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                        "idx": 1,
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                        "question_index": 1,
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                        "question": "What is the result of A - B? Please round the answer to two decimal places. ",
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                        "struct_data": "{'A': 6.755, 'B': -1.225}",
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                        "answer": 7.98,
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                        "ability": "1-digit integer with 3 decimal places"
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                    }
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                ]
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            }
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            ```
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            ##### multi-turn
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            ``` json
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            {
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                "system_prompt": "...",
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                "system_prompt_cot": "...",
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                "description": "...",
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                "data": [
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                    {
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                        "idx": 0,
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                        "multi_turn_QA": [
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                            {
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                                "turn_index": 0,
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                                "question_index": 6,
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                                "struct_data": "...",
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                                "question": "...",
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                                "answer": "F",
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                                "ability": "contextual retrieval"
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                            },
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                            {
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                                "turn_index": 1,
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                                "question_index": 6,
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                                "struct_data": "...",
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                                "question": "...",
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                                "answer": "B",
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                                "ability": "contextual retrieval"
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                            },
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                            {
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                                "turn_index": 2,
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                                "question_index": 6,
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                                "struct_data": "...",
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                                "question": "...",
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                                "answer": "A",
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                                "ability": "contextual retrieval"
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                            }
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                        ]
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                    }
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                ]
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            }
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            ```
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            ### Evaluation
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            # Dataset statistics
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