open-llm-leaderboard-old/details_tricktreat__Llama-2-7b-chat-hf-guanaco-lora

该数据集是在评估模型tricktreat/Llama-2-7b-chat-hf-guanaco-lora时自动创建的，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特定的分割存储，最新的结果存储在train分割中。此外，results配置存储了所有运行的聚合结果，用于在Open LLM Leaderboard上计算和显示聚合指标。

原始信息汇总

数据集概述

数据集简介

该数据集是在评估模型 tricktreat/Llama-2-7b-chat-hf-guanaco-lora 在 Open LLM Leaderboard 上的自动创建的。

数据集结构

• 配置数量：63个配置，每个配置对应一个评估任务。
• 数据来源：数据集从1次运行中创建，每个运行在每个配置中作为一个特定的分片存在，分片名称使用运行的时间戳。
• 分片信息：每个配置中有一个名为 "train" 的分片，指向最新的结果。
• 结果汇总：一个额外的配置 "results" 存储所有运行的汇总结果，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_tricktreat__Llama-2-7b-chat-hf-guanaco-lora", "harness_winogrande_5", split="train")

最新结果

以下是 最新结果来自2024-04-16T04:25:33.258819：

python { "all": { "acc": 0.4893443209680558, "acc_stderr": 0.034417544339580504, "acc_norm": 0.4944808333548298, "acc_norm_stderr": 0.0351790056723058, "mc1": 0.2839657282741738, "mc1_stderr": 0.015785370858396718, "mc2": 0.4382229323743104, "mc2_stderr": 0.014699763853417739 }, "harness|arc:challenge|25": { "acc": 0.4778156996587031, "acc_stderr": 0.014597001927076138, "acc_norm": 0.5264505119453925, "acc_norm_stderr": 0.01459093135812017 }, "harness|hellaswag|10": { "acc": 0.5690101573391755, "acc_stderr": 0.004942026200279591, "acc_norm": 0.7667795259908384, "acc_norm_stderr": 0.004220171569273325 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.33, "acc_stderr": 0.04725815626252605, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252605 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4444444444444444, "acc_stderr": 0.04292596718256981, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.04292596718256981 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.4868421052631579, "acc_stderr": 0.04067533136309173, "acc_norm": 0.4868421052631579, "acc_norm_stderr": 0.04067533136309173 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.539622641509434, "acc_stderr": 0.03067609659938918, "acc_norm": 0.539622641509434, "acc_norm_stderr": 0.03067609659938918 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5138888888888888, "acc_stderr": 0.041795966175810016, "acc_norm": 0.5138888888888888, "acc_norm_stderr": 0.041795966175810016 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.27, "acc_stderr": 0.044619604333847394, "acc_norm": 0.27, "acc_norm_stderr": 0.044619604333847394 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.41, "acc_stderr": 0.049431107042371025, "acc_norm": 0.41, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.3872832369942196, "acc_stderr": 0.03714325906302065, "acc_norm": 0.3872832369942196, "acc_norm_stderr": 0.03714325906302065 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.2549019607843137, "acc_stderr": 0.043364327079931785, "acc_norm": 0.2549019607843137, "acc_norm_stderr": 0.043364327079931785 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.57, "acc_stderr": 0.049756985195624284, "acc_norm": 0.57, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.43829787234042555, "acc_stderr": 0.03243618636108101, "acc_norm": 0.43829787234042555, "acc_norm_stderr": 0.03243618636108101 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.3684210526315789, "acc_stderr": 0.04537815354939392, "acc_norm": 0.3684210526315789, "acc_norm_stderr": 0.04537815354939392 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.4896551724137931, "acc_stderr": 0.04165774775728763, "acc_norm": 0.4896551724137931, "acc_norm_stderr": 0.04165774775728763 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.28835978835978837, "acc_stderr": 0.023330654054535882, "acc_norm": 0.28835978835978837, "acc_norm_stderr": 0.023330654054535882 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.25396825396825395, "acc_stderr": 0.03893259610604674, "acc_norm": 0.25396825396825395, "acc_norm_stderr": 0.03893259610604674 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.37, "acc_stderr": 0.048523658709391, "acc_norm": 0.37, "acc_norm_stderr": 0.048523658709391 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5451612903225806, "acc_stderr": 0.02832774309156107, "acc_norm": 0.5451612903225806, "acc_norm_stderr": 0.02832774309156107 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.37438423645320196, "acc_stderr": 0.03405155380561953, "acc_norm": 0.37438423645320196, "acc_norm_stderr": 0.03405155380561953 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6060606060606061, "acc_stderr": 0.03815494308688929, "acc_norm": 0.6060606060606061, "acc_norm_stderr": 0.03815494308688929 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.601010101010101, "acc_stderr": 0.034889016168527326, "acc_norm": 0.601010101010101, "acc_norm_stderr": 0.034889016168527326 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7253886010362695, "acc_stderr": 0.03221024508041153, "acc_norm": 0.7253886010362695, "acc_norm_stderr": 0.03221024508041153 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.44358974358974357, "acc_stderr": 0.025189149894764198, "acc_norm": 0.44358974358974357, "acc_norm_stderr": 0.025189149894764198 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.28888888888888886, "acc_stderr": 0.02763