open-llm-leaderboard-old/details_l3utterfly__mistral-7b-v0.1-layla-v1

该数据集是在模型 l3utterfly/mistral-7b-v0.1-layla-v1 的评估运行期间自动创建的，评估运行在 Open LLM Leaderboard 上进行。数据集由 64 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，每次运行都可以在特定配置中找到，分割名称使用运行的时间戳。train 分割始终指向最新结果。此外，results 配置存储了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。

原始信息汇总

数据集概述

数据集简介

该数据集是在对模型 l3utterfly/mistral-7b-v0.1-layla-v1 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 64 个配置，每个配置对应一个评估任务。
• 数据集由 1 次运行创建，每个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_l3utterfly__mistral-7b-v0.1-layla-v1_public", "harness_winogrande_5", split="train")

最新结果

以下是 2023-11-19T14:33:16.714547 运行的最新结果：

python { "all": { "acc": 0.5984567193500476, "acc_stderr": 0.03306896727223633, "acc_norm": 0.6069576555275077, "acc_norm_stderr": 0.03379036516702569, "mc1": 0.33659730722154224, "mc1_stderr": 0.016542412809494887, "mc2": 0.48895630003672147, "mc2_stderr": 0.01547031853751192, "em": 0.3457424496644295, "em_stderr": 0.0048706887210275595, "f1": 0.40009542785235, "f1_stderr": 0.004747563788656675 }, "harness|arc:challenge|25": { "acc": 0.5639931740614335, "acc_stderr": 0.014491225699230916, "acc_norm": 0.6015358361774744, "acc_norm_stderr": 0.014306946052735567 }, "harness|hellaswag|10": { "acc": 0.6378211511651065, "acc_stderr": 0.0047964786644038426, "acc_norm": 0.8325034853614818, "acc_norm_stderr": 0.003726554129348462 }, "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": 0.6074074074074074, "acc_stderr": 0.04218506215368881, "acc_norm": 0.6074074074074074, "acc_norm_stderr": 0.04218506215368881 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6842105263157895, "acc_stderr": 0.03782728980865469, "acc_norm": 0.6842105263157895, "acc_norm_stderr": 0.03782728980865469 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6716981132075471, "acc_stderr": 0.02890159361241178, "acc_norm": 0.6716981132075471, "acc_norm_stderr": 0.02890159361241178 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6736111111111112, "acc_stderr": 0.03921067198982266, "acc_norm": 0.6736111111111112, "acc_norm_stderr": 0.03921067198982266 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.51, "acc_stderr": 0.05024183937956911, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956911 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.33, "acc_stderr": 0.04725815626252604, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252604 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6184971098265896, "acc_stderr": 0.03703851193099521, "acc_norm": 0.6184971098265896, "acc_norm_stderr": 0.03703851193099521 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.38235294117647056, "acc_stderr": 0.04835503696107223, "acc_norm": 0.38235294117647056, "acc_norm_stderr": 0.04835503696107223 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.73, "acc_stderr": 0.044619604333847394, "acc_norm": 0.73, "acc_norm_stderr": 0.044619604333847394 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5234042553191489, "acc_stderr": 0.03265019475033582, "acc_norm": 0.5234042553191489, "acc_norm_stderr": 0.03265019475033582 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.37719298245614036, "acc_stderr": 0.04559522141958216, "acc_norm": 0.37719298245614036, "acc_norm_stderr": 0.04559522141958216 }, "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": 0.41005291005291006, "acc_stderr": 0.02533120243894444, "acc_norm": 0.41005291005291006, "acc_norm_stderr": 0.02533120243894444 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4444444444444444, "acc_stderr": 0.04444444444444449, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.04444444444444449 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6967741935483871, "acc_stderr": 0.02614868593067175, "acc_norm": 0.6967741935483871, "acc_norm_stderr": 0.02614868593067175 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.43349753694581283, "acc_stderr": 0.034867317274198714, "acc_norm": 0.43349753694581283, "acc_norm_stderr": 0.034867317274198714 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.59, "acc_stderr": 0.04943110704237101, "acc_norm": 0.59, "acc_norm_stderr": 0.04943110704237101 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6909090909090909, "acc_stderr": 0.036085410115739666, "acc_norm": 0.6909090909090909, "acc_norm_stderr": 0.036085410115739666 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7525252525252525, "acc_stderr": 0.030746300742124484, "acc_norm": 0.7525252525252525, "acc_norm_stderr": 0.030746300742124484 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8238341968911918, "acc_stderr": 0.027493504244548057, "acc_norm": 0.8238341968911918, "acc_norm_stderr": 0.027493504244548057 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5794871794871795, "acc_stderr": 0.025028610276710855, "acc_norm": 0.5794871794871795, "acc_norm_stderr": 0.025028610276