open-llm-leaderboard-old/details_kyujinpy__PlatYi-34B-Llama-Q-v2

该数据集是在模型kyujinpy/PlatYi-34B-Llama-Q-v2的评估运行期间自动创建的，用于在Open LLM Leaderboard上进行评估。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次运行中创建的，每次运行都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。此外，results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

数据集摘要

该数据集是在评估模型kyujinpy/PlatYi-34B-Llama-Q-v2在Open LLM Leaderboard上的自动创建的。

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。
• 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_kyujinpy__PlatYi-34B-Llama-Q-v2", "harness_winogrande_5", split="train")

最新结果

以下是2023-12-15T00:53:56.888909的最新结果： python { "all": { "acc": 0.7577128670517151, "acc_stderr": 0.0282619036411761, "acc_norm": 0.7647346696571936, "acc_norm_stderr": 0.028784585052284057, "mc1": 0.37821297429620565, "mc1_stderr": 0.01697633590754687, "mc2": 0.5264877146338937, "mc2_stderr": 0.014681108343134457 }, "harness|arc:challenge|25": { "acc": 0.5938566552901023, "acc_stderr": 0.014351656690097862, "acc_norm": 0.6109215017064846, "acc_norm_stderr": 0.014247309976045607 }, "harness|hellaswag|10": { "acc": 0.6506671977693687, "acc_stderr": 0.00475784902341196, "acc_norm": 0.8509261103365864, "acc_norm_stderr": 0.0035543339768972517 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.725925925925926, "acc_stderr": 0.03853254836552003, "acc_norm": 0.725925925925926, "acc_norm_stderr": 0.03853254836552003 }, "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": 0.78, "acc_stderr": 0.04163331998932261, "acc_norm": 0.78, "acc_norm_stderr": 0.04163331998932261 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.8, "acc_stderr": 0.024618298195866514, "acc_norm": 0.8, "acc_norm_stderr": 0.024618298195866514 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8888888888888888, "acc_stderr": 0.02628055093284809, "acc_norm": 0.8888888888888888, "acc_norm_stderr": 0.02628055093284809 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.65, "acc_stderr": 0.047937248544110196, "acc_norm": 0.65, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.42, "acc_stderr": 0.04960449637488583, "acc_norm": 0.42, "acc_norm_stderr": 0.04960449637488583 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7514450867052023, "acc_stderr": 0.03295304696818318, "acc_norm": 0.7514450867052023, "acc_norm_stderr": 0.03295304696818318 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.5196078431372549, "acc_stderr": 0.04971358884367405, "acc_norm": 0.5196078431372549, "acc_norm_stderr": 0.04971358884367405 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.8, "acc_stderr": 0.04020151261036846, "acc_norm": 0.8, "acc_norm_stderr": 0.04020151261036846 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.7617021276595745, "acc_stderr": 0.027851252973889778, "acc_norm": 0.7617021276595745, "acc_norm_stderr": 0.027851252973889778 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5701754385964912, "acc_stderr": 0.04657047260594963, "acc_norm": 0.5701754385964912, "acc_norm_stderr": 0.04657047260594963 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.8, "acc_stderr": 0.0333333333333333, "acc_norm": 0.8, "acc_norm_stderr": 0.0333333333333333 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.6825396825396826, "acc_stderr": 0.02397386199899207, "acc_norm": 0.6825396825396826, "acc_norm_stderr": 0.02397386199899207 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5793650793650794, "acc_stderr": 0.04415438226743745, "acc_norm": 0.5793650793650794, "acc_norm_stderr": 0.04415438226743745 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8935483870967742, "acc_stderr": 0.017545102951656635, "acc_norm": 0.8935483870967742, "acc_norm_stderr": 0.017545102951656635 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.6502463054187192, "acc_stderr": 0.03355400904969566, "acc_norm": 0.6502463054187192, "acc_norm_stderr": 0.03355400904969566 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.82, "acc_stderr": 0.038612291966536955, "acc_norm": 0.82, "acc_norm_stderr": 0.038612291966536955 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8545454545454545, "acc_stderr": 0.027530196355066584, "acc_norm": 0.8545454545454545, "acc_norm_stderr": 0.027530196355066584 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.9040404040404041, "acc_stderr": 0.020984808610047933, "acc_norm": 0.9040404040404041, "acc_norm_stderr": 0.020984808610047933 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9689119170984456, "acc_stderr": 0.012525310625527043, "acc_norm": 0.9689119170984456, "acc_norm_stderr": 0.012525310625527043 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.8128205128205128, "acc_stderr": 0.019776601086550036, "acc_norm": 0.8128205128205128, "acc_norm_stderr": 0.019776601086550036 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.42592592592592593, "acc_stderr": 0.030149135601365944, "acc_norm": 0.42592592592592593, "acc_norm_stderr": 0.030149135601365944 }, "harness|hendrycksTest-high_school_microeconomics