open-llm-leaderboard-old/details_lemon-mint__gemma-ko-7b-instruct-v0.62

该数据集是在模型 lemon-mint/gemma-ko-7b-instruct-v0.62 在 Open LLM Leaderboard 上的评估运行期间自动创建的。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2次运行中创建的，每次运行在每个配置中表示为特定的分割。train 分割始终指向最新的结果。一个名为 results 的额外配置存储了所有运行的聚合结果，这些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 Python 中的 datasets 库加载运行详情的示例。

原始信息汇总

数据集概述

该数据集是在评估模型lemon-mint/gemma-ko-7b-instruct-v0.62在Open LLM Leaderboard上的运行过程中自动创建的。

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。
• 数据集由2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。
• "train"分割总是指向最新的结果。
• 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_lemon-mint__gemma-ko-7b-instruct-v0.62", "harness_winogrande_5", split="train")

最新结果

以下是2024-04-03T13:31:01.310721运行的最新结果：

python { "all": { "acc": 0.6452999467633729, "acc_stderr": 0.03207976395932362, "acc_norm": 0.6462746893095774, "acc_norm_stderr": 0.032735425781736015, "mc1": 0.3598531211750306, "mc1_stderr": 0.016801860466677157, "mc2": 0.5111719354398984, "mc2_stderr": 0.015385094353614891 }, "harness|arc:challenge|25": { "acc": 0.5878839590443686, "acc_stderr": 0.014383915302225405, "acc_norm": 0.6331058020477816, "acc_norm_stderr": 0.0140841331181043 }, "harness|hellaswag|10": { "acc": 0.5908185620394344, "acc_stderr": 0.004906779523192673, "acc_norm": 0.7961561441943836, "acc_norm_stderr": 0.004020309191221551 }, "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": 0.5481481481481482, "acc_stderr": 0.042992689054808644, "acc_norm": 0.5481481481481482, "acc_norm_stderr": 0.042992689054808644 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.7236842105263158, "acc_stderr": 0.03639057569952928, "acc_norm": 0.7236842105263158, "acc_norm_stderr": 0.03639057569952928 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.71, "acc_stderr": 0.045604802157206845, "acc_norm": 0.71, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6830188679245283, "acc_stderr": 0.028637235639800886, "acc_norm": 0.6830188679245283, "acc_norm_stderr": 0.028637235639800886 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7222222222222222, "acc_stderr": 0.037455547914624555, "acc_norm": 0.7222222222222222, "acc_norm_stderr": 0.037455547914624555 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.44, "acc_stderr": 0.049888765156985884, "acc_norm": 0.44, "acc_norm_stderr": 0.049888765156985884 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.58, "acc_stderr": 0.049604496374885836, "acc_norm": 0.58, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "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": 0.4019607843137255, "acc_stderr": 0.048786087144669955, "acc_norm": 0.4019607843137255, "acc_norm_stderr": 0.048786087144669955 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.77, "acc_stderr": 0.04229525846816507, "acc_norm": 0.77, "acc_norm_stderr": 0.04229525846816507 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6127659574468085, "acc_stderr": 0.03184389265339526, "acc_norm": 0.6127659574468085, "acc_norm_stderr": 0.03184389265339526 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.4824561403508772, "acc_stderr": 0.04700708033551038, "acc_norm": 0.4824561403508772, "acc_norm_stderr": 0.04700708033551038 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6068965517241379, "acc_stderr": 0.040703290137070705, "acc_norm": 0.6068965517241379, "acc_norm_stderr": 0.040703290137070705 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4523809523809524, "acc_stderr": 0.02563425811555495, "acc_norm": 0.4523809523809524, "acc_norm_stderr": 0.02563425811555495 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.47619047619047616, "acc_stderr": 0.04467062628403273, "acc_norm": 0.47619047619047616, "acc_norm_stderr": 0.04467062628403273 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.43, "acc_stderr": 0.049756985195624284, "acc_norm": 0.43, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7806451612903226, "acc_stderr": 0.02354079935872329, "acc_norm": 0.7806451612903226, "acc_norm_stderr": 0.02354079935872329 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5123152709359606, "acc_stderr": 0.035169204442208966, "acc_norm": 0.5123152709359606, "acc_norm_stderr": 0.035169204442208966 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.73, "acc_stderr": 0.044619604333847394, "acc_norm": 0.73, "acc_norm_stderr": 0.044619604333847394 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.793939393939394, "acc_stderr": 0.0315841532404771, "acc_norm": 0.793939393939394, "acc_norm_stderr": 0.0315841532404771 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8232323232323232, "acc_stderr": 0.027178752639044915, "acc_norm": 0.8232323232323232, "acc_norm_stderr": 0.027178752639044915 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.927461139896373, "acc_stderr": 0.018718998520678178, "acc_norm": 0.927461139896373, "acc_norm_stderr": 0.018718998520678178 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6256410256410256, "acc_stderr": 0.024537591572830506, "acc_norm": 0.6256410256410256, "acc_norm_stderr": 0.024537591572830506 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3148148148148148, "acc_stderr": 0.02831753349606646, "acc_norm": 0.3148