open-llm-leaderboard-old/details_ChaoticNeutrals__Cookie_7B

该数据集是在模型ChaoticNeutrals/Cookie_7B在Open LLM Leaderboard上的评估运行期间自动创建的。它由63个配置组成，每个配置对应一个评估任务。数据集是从1次运行中创建的，每次运行作为每个配置中的一个特定分割，使用运行的时间戳命名。train分割始终指向最新结果。一个额外的配置results存储了运行的所有聚合结果，用于计算和显示Open LLM Leaderboard上的聚合指标。

原始信息汇总

数据集概述

数据集信息

• 数据集名称: Evaluation run of ChaoticNeutrals/Cookie_7B
• 创建目的: 该数据集是在评估模型 ChaoticNeutrals/Cookie_7B 在 Open LLM Leaderboard 上的运行过程中自动创建的。
• 数据集组成: 包含63个配置，每个配置对应一个评估任务。
• 数据来源: 数据集由1次运行创建，每次运行可以在每个配置中找到特定的分割，分割名称使用运行的时间戳。"train" 分割始终指向最新的结果。
• 额外配置: 一个名为 "results" 的额外配置存储了所有运行的聚合结果，用于计算和显示在 Open LLM Leaderboard 上的聚合指标。

数据加载示例

python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_ChaoticNeutrals__Cookie_7B", "harness_winogrande_5", split="train")

最新结果

• 最新结果来源: 2024-02-21T07:19:11.368453
• 结果示例: python { "all": { "acc": 0.6489384774347392, "acc_stderr": 0.032131421920616465, "acc_norm": 0.6498781521461111, "acc_norm_stderr": 0.032783132740631354, "mc1": 0.5128518971848225, "mc1_stderr": 0.01749771794429982, "mc2": 0.6687534212220169, "mc2_stderr": 0.015263939252034519 }, "harness|arc:challenge|25": { "acc": 0.6791808873720137, "acc_stderr": 0.01364094309194653, "acc_norm": 0.697098976109215, "acc_norm_stderr": 0.013428241573185349 }, "harness|hellaswag|10": { "acc": 0.7105158334993029, "acc_stderr": 0.004525960965551707, "acc_norm": 0.8757219677355108, "acc_norm_stderr": 0.0032922425436373417 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6222222222222222, "acc_stderr": 0.04188307537595853, "acc_norm": 0.6222222222222222, "acc_norm_stderr": 0.04188307537595853 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.7171052631578947, "acc_stderr": 0.03665349695640767, "acc_norm": 0.7171052631578947, "acc_norm_stderr": 0.03665349695640767 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.61, "acc_stderr": 0.04902071300001975, "acc_norm": 0.61, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7132075471698113, "acc_stderr": 0.027834912527544067, "acc_norm": 0.7132075471698113, "acc_norm_stderr": 0.027834912527544067 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7430555555555556, "acc_stderr": 0.03653946969442099, "acc_norm": 0.7430555555555556, "acc_norm_stderr": 0.03653946969442099 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.47, "acc_stderr": 0.050161355804659205, "acc_norm": 0.47, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.54, "acc_stderr": 0.05009082659620333, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6705202312138728, "acc_stderr": 0.03583901754736412, "acc_norm": 0.6705202312138728, "acc_norm_stderr": 0.03583901754736412 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.38235294117647056, "acc_stderr": 0.04835503696107224, "acc_norm": 0.38235294117647056, "acc_norm_stderr": 0.04835503696107224 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.76, "acc_stderr": 0.042923469599092816, "acc_norm": 0.76, "acc_norm_stderr": 0.042923469599092816 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.574468085106383, "acc_stderr": 0.03232146916224469, "acc_norm": 0.574468085106383, "acc_norm_stderr": 0.03232146916224469 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.4824561403508772, "acc_stderr": 0.04700708033551038, "acc_norm": 0.4824561403508772, "acc_norm_stderr": 0.04700708033551038 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5379310344827586, "acc_stderr": 0.04154659671707548, "acc_norm": 0.5379310344827586, "acc_norm_stderr": 0.04154659671707548 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.41005291005291006, "acc_stderr": 0.02533120243894443, "acc_norm": 0.41005291005291006, "acc_norm_stderr": 0.02533120243894443 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4126984126984127, "acc_stderr": 0.04403438954768177, "acc_norm": 0.4126984126984127, "acc_norm_stderr": 0.04403438954768177 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7870967741935484, "acc_stderr": 0.023287665127268545, "acc_norm": 0.7870967741935484, "acc_norm_stderr": 0.023287665127268545 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5320197044334976, "acc_stderr": 0.03510766597959215, "acc_norm": 0.5320197044334976, "acc_norm_stderr": 0.03510766597959215 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.68, "acc_stderr": 0.04688261722621505, "acc_norm": 0.68, "acc_norm_stderr": 0.04688261722621505 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7818181818181819, "acc_stderr": 0.03225078108306289, "acc_norm": 0.7818181818181819, "acc_norm_stderr": 0.03225078108306289 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.797979797979798, "acc_stderr": 0.028606204289229865, "acc_norm": 0.797979797979798, "acc_norm_stderr": 0.028606204289229865 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8756476683937824, "acc_stderr": 0.023814477086593552, "acc_norm": 0.8756476683937824, "acc_norm_stderr": 0.023814477086593552 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6615384615384615, "acc_stderr": 0.023991500500313036, "acc_norm": 0.6615384615384615, "acc_norm_stderr": 0.023991500500313036 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.337037037037037, "acc_stderr": 0.02882088466625326, "acc_norm": 0.337037037037037,