open-llm-leaderboard-old/details_vilm__Mixsmol-4x400M-v0.1-epoch2

该数据集是在Open LLM Leaderboard上对模型vilm/Mixsmol-4x400M-v0.1-epoch2进行评估时自动创建的。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，分割以运行的时间戳命名。train分割始终指向最新的结果。此外，一个名为results的配置存储了所有运行的聚合结果，并用于计算和显示Open LLM Leaderboard上的聚合指标。

原始信息汇总

数据集概述

该数据集是在评估模型 vilm/Mixsmol-4x400M-v0.1-epoch2 在 Open LLM Leaderboard 上的运行过程中自动创建的。

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 1 次运行中创建，每个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。
• 额外的 "results" 配置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_vilm__Mixsmol-4x400M-v0.1-epoch2", "harness_winogrande_5", split="train")

最新结果

以下是 2024-02-01T20:12:11.132226 运行的最新结果：

python { "all": { "acc": 0.25283618854191925, "acc_stderr": 0.03066762235665367, "acc_norm": 0.25354322916408834, "acc_norm_stderr": 0.03146102376966158, "mc1": 0.20318237454100369, "mc1_stderr": 0.014085666526340886, "mc2": 0.3923567669357625, "mc2_stderr": 0.014714668526801372 }, "harness|arc:challenge|25": { "acc": 0.20051194539249148, "acc_stderr": 0.011700318050499382, "acc_norm": 0.2354948805460751, "acc_norm_stderr": 0.01239945185500475 }, "harness|hellaswag|10": { "acc": 0.2962557259510058, "acc_stderr": 0.004556719864763093, "acc_norm": 0.3260306711810396, "acc_norm_stderr": 0.004678006403691724 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.23, "acc_stderr": 0.04229525846816506, "acc_norm": 0.23, "acc_norm_stderr": 0.04229525846816506 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.2, "acc_stderr": 0.034554737023254366, "acc_norm": 0.2, "acc_norm_stderr": 0.034554737023254366 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.17763157894736842, "acc_stderr": 0.031103182383123398, "acc_norm": 0.17763157894736842, "acc_norm_stderr": 0.031103182383123398 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.29, "acc_stderr": 0.04560480215720683, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720683 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.22264150943396227, "acc_stderr": 0.025604233470899098, "acc_norm": 0.22264150943396227, "acc_norm_stderr": 0.025604233470899098 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.24305555555555555, "acc_stderr": 0.03586879280080343, "acc_norm": 0.24305555555555555, "acc_norm_stderr": 0.03586879280080343 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.17, "acc_stderr": 0.03775251680686371, "acc_norm": 0.17, "acc_norm_stderr": 0.03775251680686371 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.24, "acc_stderr": 0.04292346959909283, "acc_norm": 0.24, "acc_norm_stderr": 0.04292346959909283 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.32, "acc_stderr": 0.04688261722621503, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621503 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.2832369942196532, "acc_stderr": 0.03435568056047874, "acc_norm": 0.2832369942196532, "acc_norm_stderr": 0.03435568056047874 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.23529411764705882, "acc_stderr": 0.04220773659171453, "acc_norm": 0.23529411764705882, "acc_norm_stderr": 0.04220773659171453 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.21, "acc_stderr": 0.04093601807403326, "acc_norm": 0.21, "acc_norm_stderr": 0.04093601807403326 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.26382978723404255, "acc_stderr": 0.02880998985410297, "acc_norm": 0.26382978723404255, "acc_norm_stderr": 0.02880998985410297 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2719298245614035, "acc_stderr": 0.041857744240220554, "acc_norm": 0.2719298245614035, "acc_norm_stderr": 0.041857744240220554 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.22758620689655173, "acc_stderr": 0.03493950380131183, "acc_norm": 0.22758620689655173, "acc_norm_stderr": 0.03493950380131183 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.24603174603174602, "acc_stderr": 0.022182037202948365, "acc_norm": 0.24603174603174602, "acc_norm_stderr": 0.022182037202948365 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.15873015873015872, "acc_stderr": 0.032684540130117436, "acc_norm": 0.15873015873015872, "acc_norm_stderr": 0.032684540130117436 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.18, "acc_stderr": 0.038612291966536934, "acc_norm": 0.18, "acc_norm_stderr": 0.038612291966536934 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.3064516129032258, "acc_stderr": 0.026226485652553883, "acc_norm": 0.3064516129032258, "acc_norm_stderr": 0.026226485652553883 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.2955665024630542, "acc_stderr": 0.032104944337514575, "acc_norm": 0.2955665024630542, "acc_norm_stderr": 0.032104944337514575 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.21818181818181817, "acc_stderr": 0.03225078108306289, "acc_norm": 0.21818181818181817, "acc_norm_stderr": 0.03225078108306289 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.25757575757575757, "acc_stderr": 0.031156269519646826, "acc_norm": 0.25757575757575757, "acc_norm_stderr": 0.031156269519646826 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.34196891191709844, "acc_stderr": 0.03423465100104281, "acc_norm": 0.34196891191709844, "acc_norm_stderr": 0.03423465100104281 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.26153846153846155, "acc_stderr": 0.02228214120420442, "acc_norm": 0.26153846153846155, "acc_norm_stderr": 0.02228214120420442 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.26296296296296295, "acc_stderr": 0.026842057873833706, "acc_norm":