open-llm-leaderboard-old/details_SF-Foundation__Ein-72B-v0.11

该数据集是在Open LLM Leaderboard上对模型SF-Foundation/Ein-72B-v0.11进行评估时自动创建的。数据集由63个配置组成，每个配置对应一个评估任务。数据集是从1次运行中生成的，每次运行都作为每个配置中的一个特定分割存储，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，用于计算和显示Open LLM Leaderboard上的聚合指标。README还提供了如何使用`datasets`库中的`load_dataset`函数加载运行详情的示例。

原始信息汇总

数据集概述

数据集简介

该数据集是在模型SF-Foundation/Ein-72B-v0.11的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1次运行中创建，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。
• 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_SF-Foundation__Ein-72B-v0.11", "harness_winogrande_5", split="train")

最新结果

以下是2024-02-11T13:40:58.813057的最新结果：

python { "all": { "acc": 0.772373168297044, "acc_stderr": 0.028022585208284104, "acc_norm": 0.7739457676486081, "acc_norm_stderr": 0.02857928542974863, "mc1": 0.6634026927784578, "mc1_stderr": 0.016542412809494887, "mc2": 0.790182015835219, "mc2_stderr": 0.013777445073321324 }, "harness|arc:challenge|25": { "acc": 0.7474402730375427, "acc_stderr": 0.012696728980207704, "acc_norm": 0.7679180887372014, "acc_norm_stderr": 0.012336718284948856 }, "harness|hellaswag|10": { "acc": 0.7343158733320055, "acc_stderr": 0.004407941058874964, "acc_norm": 0.890161322445728, "acc_norm_stderr": 0.003120495238827559 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.7185185185185186, "acc_stderr": 0.038850042458002526, "acc_norm": 0.7185185185185186, "acc_norm_stderr": 0.038850042458002526 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.881578947368421, "acc_stderr": 0.026293995855474928, "acc_norm": 0.881578947368421, "acc_norm_stderr": 0.026293995855474928 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.82, "acc_stderr": 0.038612291966536955, "acc_norm": 0.82, "acc_norm_stderr": 0.038612291966536955 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.8377358490566038, "acc_stderr": 0.02269148287203535, "acc_norm": 0.8377358490566038, "acc_norm_stderr": 0.02269148287203535 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.9375, "acc_stderr": 0.02024219611347799, "acc_norm": 0.9375, "acc_norm_stderr": 0.02024219611347799 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.62, "acc_stderr": 0.04878317312145633, "acc_norm": 0.62, "acc_norm_stderr": 0.04878317312145633 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7514450867052023, "acc_stderr": 0.03295304696818317, "acc_norm": 0.7514450867052023, "acc_norm_stderr": 0.03295304696818317 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.5686274509803921, "acc_stderr": 0.04928099597287534, "acc_norm": 0.5686274509803921, "acc_norm_stderr": 0.04928099597287534 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.81, "acc_stderr": 0.03942772444036622, "acc_norm": 0.81, "acc_norm_stderr": 0.03942772444036622 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.8, "acc_stderr": 0.026148818018424506, "acc_norm": 0.8, "acc_norm_stderr": 0.026148818018424506 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.6052631578947368, "acc_stderr": 0.045981880578165414, "acc_norm": 0.6052631578947368, "acc_norm_stderr": 0.045981880578165414 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.7793103448275862, "acc_stderr": 0.0345593020192481, "acc_norm": 0.7793103448275862, "acc_norm_stderr": 0.0345593020192481 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.6825396825396826, "acc_stderr": 0.023973861998992072, "acc_norm": 0.6825396825396826, "acc_norm_stderr": 0.023973861998992072 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5634920634920635, "acc_stderr": 0.04435932892851466, "acc_norm": 0.5634920634920635, "acc_norm_stderr": 0.04435932892851466 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.53, "acc_stderr": 0.050161355804659205, "acc_norm": 0.53, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8870967741935484, "acc_stderr": 0.01800360332586361, "acc_norm": 0.8870967741935484, "acc_norm_stderr": 0.01800360332586361 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.6600985221674877, "acc_stderr": 0.033327690684107895, "acc_norm": 0.6600985221674877, "acc_norm_stderr": 0.033327690684107895 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.82, "acc_stderr": 0.038612291966536934, "acc_norm": 0.82, "acc_norm_stderr": 0.038612291966536934 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8606060606060606, "acc_stderr": 0.027045948825865394, "acc_norm": 0.8606060606060606, "acc_norm_stderr": 0.027045948825865394 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.9393939393939394, "acc_stderr": 0.016999994927421592, "acc_norm": 0.9393939393939394, "acc_norm_stderr": 0.016999994927421592 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9844559585492227, "acc_stderr": 0.008927492715084315, "acc_norm": 0.9844559585492227, "acc_norm_stderr": 0.008927492715084315 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.8051282051282052, "acc_stderr": 0.020083167595181393, "acc_norm": 0.8051282051282052, "acc_norm_stderr": 0.020083167595181393 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.45925925925925926, "acc_stderr": 0.030384169232350818, "acc_norm": 0.45925925925925926, "acc_norm_stderr": 0.030384169232350818 }, "harness|hendrycksTest-high_school_microeconomics|5": {