open-llm-leaderboard-old/details_abhishekchohan__mistral-7B-med-merge

该数据集是在评估模型abhishekchohan/mistral-7B-med-merge时自动生成的，评估是在Open LLM Leaderboard上进行的。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次运行生成，每次运行的结果存储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，用于在Open LLM Leaderboard上计算和显示聚合指标。

原始信息汇总

数据集概述

数据集简介

该数据集是在评估模型abhishekchohan/mistral-7B-med-merge在Open LLM Leaderboard上的运行过程中自动创建的。

数据集结构

• 配置数量：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。
• 最新结果："train"分割始终指向最新的结果。
• 聚合结果：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_abhishekchohan__mistral-7B-med-merge", "harness_winogrande_5", split="train")

最新结果

以下是最新结果（来自2024-01-21T23:55:53.444793的运行）：

python { "all": { "acc": 0.5813577401888572, "acc_stderr": 0.03392117164078901, "acc_norm": 0.5837504497394033, "acc_norm_stderr": 0.03462209771980794, "mc1": 0.3880048959608323, "mc1_stderr": 0.017058761501347976, "mc2": 0.536535823977723, "mc2_stderr": 0.015589392373408393 }, "harness|arc:challenge|25": { "acc": 0.6143344709897611, "acc_stderr": 0.014224250973257187, "acc_norm": 0.6450511945392492, "acc_norm_stderr": 0.013983036904094089 }, "harness|hellaswag|10": { "acc": 0.6461860187213703, "acc_stderr": 0.004771751187407019, "acc_norm": 0.8296156144194383, "acc_norm_stderr": 0.0037520176390837515 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5851851851851851, "acc_stderr": 0.04256193767901408, "acc_norm": 0.5851851851851851, "acc_norm_stderr": 0.04256193767901408 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.631578947368421, "acc_stderr": 0.03925523381052932, "acc_norm": 0.631578947368421, "acc_norm_stderr": 0.03925523381052932 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.6, "acc_stderr": 0.04923659639173309, "acc_norm": 0.6, "acc_norm_stderr": 0.04923659639173309 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6113207547169811, "acc_stderr": 0.030000485448675986, "acc_norm": 0.6113207547169811, "acc_norm_stderr": 0.030000485448675986 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6458333333333334, "acc_stderr": 0.039994111357535424, "acc_norm": 0.6458333333333334, "acc_norm_stderr": 0.039994111357535424 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.39, "acc_stderr": 0.04902071300001974, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001974 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5549132947976878, "acc_stderr": 0.03789401760283647, "acc_norm": 0.5549132947976878, "acc_norm_stderr": 0.03789401760283647 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3235294117647059, "acc_stderr": 0.04655010411319616, "acc_norm": 0.3235294117647059, "acc_norm_stderr": 0.04655010411319616 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.65, "acc_stderr": 0.047937248544110196, "acc_norm": 0.65, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5702127659574469, "acc_stderr": 0.03236214467715564, "acc_norm": 0.5702127659574469, "acc_norm_stderr": 0.03236214467715564 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.38596491228070173, "acc_stderr": 0.04579639422070434, "acc_norm": 0.38596491228070173, "acc_norm_stderr": 0.04579639422070434 }, "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": 0.42857142857142855, "acc_stderr": 0.025487187147859375, "acc_norm": 0.42857142857142855, "acc_norm_stderr": 0.025487187147859375 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.35714285714285715, "acc_stderr": 0.042857142857142816, "acc_norm": 0.35714285714285715, "acc_norm_stderr": 0.042857142857142816 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6806451612903226, "acc_stderr": 0.026522709674667768, "acc_norm": 0.6806451612903226, "acc_norm_stderr": 0.026522709674667768 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4433497536945813, "acc_stderr": 0.03495334582162933, "acc_norm": 0.4433497536945813, "acc_norm_stderr": 0.03495334582162933 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.65, "acc_stderr": 0.047937248544110196, "acc_norm": 0.65, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6848484848484848, "acc_stderr": 0.0362773057502241, "acc_norm": 0.6848484848484848, "acc_norm_stderr": 0.0362773057502241 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7070707070707071, "acc_stderr": 0.03242497958178816, "acc_norm": 0.7070707070707071, "acc_norm_stderr": 0.03242497958178816 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7668393782383419, "acc_stderr": 0.03051611137147601, "acc_norm": 0.7668393782383419, "acc_norm_stderr": 0.03051611137147601 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5512820512820513, "acc_stderr": 0.025217315184846486, "acc_norm": 0.5512820512820513, "acc_norm_stderr": 0.025217315184846486 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3148148148148148, "acc_stderr": 0.02831753349606648, "acc_norm": 0.3