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

该数据集是在评估模型abhishekchohan/mistral-7B-forest-merge时自动生成的，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，用于计算和展示在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 abhishekchohan/mistral-7B-forest-merge 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。
• 数据集由 2 次运行创建，每次运行的结果可以在每个配置中找到，以运行的时间戳命名的特定分片形式存储。
• 每个配置中的 "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-forest-merge", "harness_winogrande_5", split="train")

最新结果

以下是 最新结果 的摘要：

python { "all": { "acc": 0.6022067316089463, "acc_stderr": 0.032877722301518426, "acc_norm": 0.6045609403878123, "acc_norm_stderr": 0.03353760382711908, "mc1": 0.41615667074663404, "mc1_stderr": 0.017255657502903043, "mc2": 0.5748469157653282, "mc2_stderr": 0.015758784357589765 }, "harness|arc:challenge|25": { "acc": 0.6049488054607508, "acc_stderr": 0.014285898292938167, "acc_norm": 0.636518771331058, "acc_norm_stderr": 0.014056207319068285 }, "harness|hellaswag|10": { "acc": 0.6519617606054571, "acc_stderr": 0.004753746951620151, "acc_norm": 0.8440549691296555, "acc_norm_stderr": 0.0036206175507473956 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.562962962962963, "acc_stderr": 0.04284958639753401, "acc_norm": 0.562962962962963, "acc_norm_stderr": 0.04284958639753401 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6578947368421053, "acc_stderr": 0.03860731599316092, "acc_norm": 0.6578947368421053, "acc_norm_stderr": 0.03860731599316092 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.61, "acc_stderr": 0.04902071300001975, "acc_norm": 0.61, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6679245283018868, "acc_stderr": 0.02898545565233439, "acc_norm": 0.6679245283018868, "acc_norm_stderr": 0.02898545565233439 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6597222222222222, "acc_stderr": 0.039621355734862175, "acc_norm": 0.6597222222222222, "acc_norm_stderr": 0.039621355734862175 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.41, "acc_stderr": 0.049431107042371025, "acc_norm": 0.41, "acc_norm_stderr": 0.049431107042371025 }, "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": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5953757225433526, "acc_stderr": 0.03742461193887248, "acc_norm": 0.5953757225433526, "acc_norm_stderr": 0.03742461193887248 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3431372549019608, "acc_stderr": 0.04724007352383888, "acc_norm": 0.3431372549019608, "acc_norm_stderr": 0.04724007352383888 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.79, "acc_stderr": 0.04093601807403326, "acc_norm": 0.79, "acc_norm_stderr": 0.04093601807403326 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5148936170212766, "acc_stderr": 0.03267151848924777, "acc_norm": 0.5148936170212766, "acc_norm_stderr": 0.03267151848924777 }, "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": 0.5241379310344828, "acc_stderr": 0.0416180850350153, "acc_norm": 0.5241379310344828, "acc_norm_stderr": 0.0416180850350153 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4074074074074074, "acc_stderr": 0.025305906241590632, "acc_norm": 0.4074074074074074, "acc_norm_stderr": 0.025305906241590632 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.42063492063492064, "acc_stderr": 0.04415438226743744, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.04415438226743744 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7161290322580646, "acc_stderr": 0.02564938106302927, "acc_norm": 0.7161290322580646, "acc_norm_stderr": 0.02564938106302927 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4187192118226601, "acc_stderr": 0.034711928605184676, "acc_norm": 0.4187192118226601, "acc_norm_stderr": 0.034711928605184676 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.67, "acc_stderr": 0.047258156262526094, "acc_norm": 0.67, "acc_norm_stderr": 0.047258156262526094 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7333333333333333, "acc_stderr": 0.03453131801885417, "acc_norm": 0.7333333333333333, "acc_norm_stderr": 0.03453131801885417 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7323232323232324, "acc_stderr": 0.03154449888270285, "acc_norm": 0.7323232323232324, "acc_norm_stderr": 0.03154449888270285 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8134715025906736, "acc_stderr": 0.028112091210117467, "acc_norm": 0.8134715025906736, "acc_norm_stderr": 0.028112091210117467 }, "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": 0.29259259259259257, "acc_stderr": 0.027738969632176088, "acc_norm": 0.29259259259259257, "acc_norm_stderr": 0.027738969632176088 }, "harness