open-llm-leaderboard-old/details_deepseek-ai__deepseek-llm-7b-chat

该数据集是在评估模型deepseek-ai/deepseek-llm-7b-chat时自动创建的，主要用于Open LLM Leaderboard的评估任务。数据集包含63个配置，每个配置对应一个评估任务。数据集由2次运行生成，每次运行的结果作为特定配置中的一个分割，分割名称使用运行的时间戳。train分割始终指向最新的结果。此外，还有一个名为results的配置，存储了所有运行的聚合结果，用于计算和展示Open LLM Leaderboard上的聚合指标。

原始信息汇总

数据集概述

数据集摘要

该数据集是在对模型 deepseek-ai/deepseek-llm-7b-chat 进行评估运行期间自动创建的，用于 Open LLM Leaderboard。

数据集组成

• 数据集包含 63 个配置，每个配置对应一个评估任务。
• 数据集从 2 次运行中创建，每次运行可以在每个配置中作为一个特定的分割找到，分割名称使用运行的时间戳。
• "train" 分割始终指向最新的结果。
• 一个额外的配置 "results" 存储所有运行的聚合结果，用于计算和显示 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_deepseek-ai__deepseek-llm-7b-chat", "harness_winogrande_5", split="train")

最新结果

这些是最新的结果，来自 2024-01-05T10:38:25.592014 的运行： python { "all": { "acc": 0.5217428488143239, "acc_stderr": 0.03404743889765096, "acc_norm": 0.5230686740068565, "acc_norm_stderr": 0.0347462652663857, "mc1": 0.33659730722154224, "mc1_stderr": 0.016542412809494887, "mc2": 0.47921745550580336, "mc2_stderr": 0.015430955018425466 }, "harness|arc:challenge|25": { "acc": 0.5119453924914675, "acc_stderr": 0.014607220340597167, "acc_norm": 0.5571672354948806, "acc_norm_stderr": 0.014515573873348899 }, "harness|hellaswag|10": { "acc": 0.5957976498705437, "acc_stderr": 0.0048973407933143795, "acc_norm": 0.7937661820354511, "acc_norm_stderr": 0.0040377344515556465 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.45925925925925926, "acc_stderr": 0.04304979692464242, "acc_norm": 0.45925925925925926, "acc_norm_stderr": 0.04304979692464242 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5263157894736842, "acc_stderr": 0.04063302731486671, "acc_norm": 0.5263157894736842, "acc_norm_stderr": 0.04063302731486671 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.55, "acc_stderr": 0.049999999999999996, "acc_norm": 0.55, "acc_norm_stderr": 0.049999999999999996 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5320754716981132, "acc_stderr": 0.030709486992556545, "acc_norm": 0.5320754716981132, "acc_norm_stderr": 0.030709486992556545 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5, "acc_stderr": 0.04181210050035455, "acc_norm": 0.5, "acc_norm_stderr": 0.04181210050035455 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.37, "acc_stderr": 0.048523658709391, "acc_norm": 0.37, "acc_norm_stderr": 0.048523658709391 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.4913294797687861, "acc_stderr": 0.03811890988940412, "acc_norm": 0.4913294797687861, "acc_norm_stderr": 0.03811890988940412 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.29411764705882354, "acc_stderr": 0.04533838195929776, "acc_norm": 0.29411764705882354, "acc_norm_stderr": 0.04533838195929776 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.62, "acc_stderr": 0.048783173121456316, "acc_norm": 0.62, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4340425531914894, "acc_stderr": 0.03240038086792747, "acc_norm": 0.4340425531914894, "acc_norm_stderr": 0.03240038086792747 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2719298245614035, "acc_stderr": 0.04185774424022056, "acc_norm": 0.2719298245614035, "acc_norm_stderr": 0.04185774424022056 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.45517241379310347, "acc_stderr": 0.04149886942192117, "acc_norm": 0.45517241379310347, "acc_norm_stderr": 0.04149886942192117 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.31216931216931215, "acc_stderr": 0.023865206836972602, "acc_norm": 0.31216931216931215, "acc_norm_stderr": 0.023865206836972602 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3333333333333333, "acc_stderr": 0.04216370213557835, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04216370213557835 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5709677419354838, "acc_stderr": 0.028156036538233193, "acc_norm": 0.5709677419354838, "acc_norm_stderr": 0.028156036538233193 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.3497536945812808, "acc_stderr": 0.03355400904969565, "acc_norm": 0.3497536945812808, "acc_norm_stderr": 0.03355400904969565 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.47, "acc_stderr": 0.050161355804659205, "acc_norm": 0.47, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6787878787878788, "acc_stderr": 0.03646204963253812, "acc_norm": 0.6787878787878788, "acc_norm_stderr": 0.03646204963253812 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6717171717171717, "acc_stderr": 0.03345678422756775, "acc_norm": 0.6717171717171717, "acc_norm_stderr": 0.03345678422756775 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7150259067357513, "acc_stderr": 0.03257714077709662, "acc_norm": 0.7150259067357513, "acc_norm_stderr": 0.03257714077709662 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.4666666666666667, "acc_stderr": 0.025294608023986472, "acc_norm": 0.4666666666666667, "acc_norm_stderr": 0.025294608023986472 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3, "acc_stderr": 0.027940457136228423, "acc_norm": 0.3, "acc_norm_stderr": 0.027940457136228423 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.47478991596638653, "acc_stderr": 0.032437180551374095, "acc_norm": 0.4747899