open-llm-leaderboard-old/details_ChavyvAkvar__llama-3-habib

该数据集是在评估模型ChavyvAkvar/llama-3-habib时自动创建的，主要用于在Open LLM Leaderboard上展示评估结果。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，每次运行的结果作为一个特定的分割存储，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，用于计算和展示Open LLM Leaderboard上的聚合指标。

原始信息汇总

数据集概述

该数据集是在对模型 ChavyvAkvar/llama-3-habib 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。
• 数据集是从 1 次运行中创建的。每个运行可以在每个配置中作为一个特定的分片找到，分片名称使用运行的时间戳。
• "train" 分片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_ChavyvAkvar__llama-3-habib", "harness_winogrande_5", split="train")

最新结果

以下是 2024-04-20T21:28:22.628929 运行的最新结果：

python { "all": { "acc": 0.6226250897152034, "acc_stderr": 0.03287644266473216, "acc_norm": 0.6250375088429165, "acc_norm_stderr": 0.03352918895536386, "mc1": 0.3108935128518972, "mc1_stderr": 0.016203316673559696, "mc2": 0.4652961574435364, "mc2_stderr": 0.015515027057591987 }, "harness|arc:challenge|25": { "acc": 0.5725255972696246, "acc_stderr": 0.014456862944650647, "acc_norm": 0.5989761092150171, "acc_norm_stderr": 0.014322255790719865 }, "harness|hellaswag|10": { "acc": 0.6094403505277833, "acc_stderr": 0.004868787333436584, "acc_norm": 0.7829117705636327, "acc_norm_stderr": 0.004114206310339745 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5333333333333333, "acc_stderr": 0.043097329010363554, "acc_norm": 0.5333333333333333, "acc_norm_stderr": 0.043097329010363554 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5855263157894737, "acc_stderr": 0.04008973785779205, "acc_norm": 0.5855263157894737, "acc_norm_stderr": 0.04008973785779205 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.63, "acc_stderr": 0.04852365870939099, "acc_norm": 0.63, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7094339622641509, "acc_stderr": 0.027943219989337145, "acc_norm": 0.7094339622641509, "acc_norm_stderr": 0.027943219989337145 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7638888888888888, "acc_stderr": 0.03551446610810826, "acc_norm": 0.7638888888888888, "acc_norm_stderr": 0.03551446610810826 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.41, "acc_stderr": 0.04943110704237102, "acc_norm": 0.41, "acc_norm_stderr": 0.04943110704237102 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6069364161849711, "acc_stderr": 0.03724249595817731, "acc_norm": 0.6069364161849711, "acc_norm_stderr": 0.03724249595817731 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.45098039215686275, "acc_stderr": 0.04951218252396262, "acc_norm": 0.45098039215686275, "acc_norm_stderr": 0.04951218252396262 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5574468085106383, "acc_stderr": 0.03246956919789958, "acc_norm": 0.5574468085106383, "acc_norm_stderr": 0.03246956919789958 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5350877192982456, "acc_stderr": 0.046920083813689104, "acc_norm": 0.5350877192982456, "acc_norm_stderr": 0.046920083813689104 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6068965517241379, "acc_stderr": 0.0407032901370707, "acc_norm": 0.6068965517241379, "acc_norm_stderr": 0.0407032901370707 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.40476190476190477, "acc_stderr": 0.02527985039740491, "acc_norm": 0.40476190476190477, "acc_norm_stderr": 0.02527985039740491 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.42063492063492064, "acc_stderr": 0.04415438226743743, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.04415438226743743 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7322580645161291, "acc_stderr": 0.025189006660212385, "acc_norm": 0.7322580645161291, "acc_norm_stderr": 0.025189006660212385 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4630541871921182, "acc_stderr": 0.035083705204426656, "acc_norm": 0.4630541871921182, "acc_norm_stderr": 0.035083705204426656 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7575757575757576, "acc_stderr": 0.03346409881055953, "acc_norm": 0.7575757575757576, "acc_norm_stderr": 0.03346409881055953 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7626262626262627, "acc_stderr": 0.030313710538198906, "acc_norm": 0.7626262626262627, "acc_norm_stderr": 0.030313710538198906 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8549222797927462, "acc_stderr": 0.02541634309630645, "acc_norm": 0.8549222797927462, "acc_norm_stderr": 0.02541634309630645 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5769230769230769, "acc_stderr": 0.02504919787604234, "acc_norm": 0.5769230769230769, "acc_norm_stderr": 0.02504919787604234 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.362962962962963, "acc_stderr": 0.02931820364520686, "acc_norm": 0.362962962962963, "acc_norm_stderr": 0.