open-llm-leaderboard-old/details_APMIC__caigun-lora-model-34B-v3

该数据集是在APMIC/caigun-lora-model-34B-v3模型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。数据集来源于一次运行，每次运行都作为一个特定的分割，以运行的时间戳命名。train分割始终指向最新的结果。此外，还有一个results配置，存储了运行中的所有聚合结果，用于在Open LLM排行榜上计算和显示聚合指标。文件还包含了如何加载数据集和特定运行的最新结果的示例。

原始信息汇总

数据集概述

数据集摘要

该数据集是在模型 APMIC/caigun-lora-model-34B-v3 的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。
• 数据集从 1 次运行中创建，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_APMIC__caigun-lora-model-34B-v3", "harness_winogrande_5", split="train")

最新结果

以下是 2023-12-23T18:31:31.662412 运行的最新结果：

python { "all": { "acc": 0.7483676764475267, "acc_stderr": 0.028542757366816985, "acc_norm": 0.754246296187874, "acc_norm_stderr": 0.029076189504433473, "mc1": 0.401468788249694, "mc1_stderr": 0.017160273901693654, "mc2": 0.5646830588696623, "mc2_stderr": 0.014942367992340418 }, "harness|arc:challenge|25": { "acc": 0.6356655290102389, "acc_stderr": 0.014063260279882419, "acc_norm": 0.6689419795221843, "acc_norm_stderr": 0.013752062419817829 }, "harness|hellaswag|10": { "acc": 0.6499701254730134, "acc_stderr": 0.004760041843651487, "acc_norm": 0.8477394941246763, "acc_norm_stderr": 0.003585389636472376 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.43, "acc_stderr": 0.049756985195624284, "acc_norm": 0.43, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.7111111111111111, "acc_stderr": 0.0391545063041425, "acc_norm": 0.7111111111111111, "acc_norm_stderr": 0.0391545063041425 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.8881578947368421, "acc_stderr": 0.02564834125169361, "acc_norm": 0.8881578947368421, "acc_norm_stderr": 0.02564834125169361 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.79, "acc_stderr": 0.040936018074033256, "acc_norm": 0.79, "acc_norm_stderr": 0.040936018074033256 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7924528301886793, "acc_stderr": 0.02495991802891127, "acc_norm": 0.7924528301886793, "acc_norm_stderr": 0.02495991802891127 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8611111111111112, "acc_stderr": 0.028919802956134902, "acc_norm": 0.8611111111111112, "acc_norm_stderr": 0.028919802956134902 }, "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": 0.63, "acc_stderr": 0.048523658709391, "acc_norm": 0.63, "acc_norm_stderr": 0.048523658709391 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.41, "acc_stderr": 0.049431107042371025, "acc_norm": 0.41, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7283236994219653, "acc_stderr": 0.03391750322321659, "acc_norm": 0.7283236994219653, "acc_norm_stderr": 0.03391750322321659 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.46078431372549017, "acc_stderr": 0.049598599663841815, "acc_norm": 0.46078431372549017, "acc_norm_stderr": 0.049598599663841815 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.82, "acc_stderr": 0.03861229196653694, "acc_norm": 0.82, "acc_norm_stderr": 0.03861229196653694 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.7489361702127659, "acc_stderr": 0.028346963777162452, "acc_norm": 0.7489361702127659, "acc_norm_stderr": 0.028346963777162452 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5877192982456141, "acc_stderr": 0.04630653203366596, "acc_norm": 0.5877192982456141, "acc_norm_stderr": 0.04630653203366596 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.7793103448275862, "acc_stderr": 0.03455930201924812, "acc_norm": 0.7793103448275862, "acc_norm_stderr": 0.03455930201924812 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.6375661375661376, "acc_stderr": 0.02475747390275205, "acc_norm": 0.6375661375661376, "acc_norm_stderr": 0.02475747390275205 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5634920634920635, "acc_stderr": 0.04435932892851466, "acc_norm": 0.5634920634920635, "acc_norm_stderr": 0.04435932892851466 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.54, "acc_stderr": 0.05009082659620333, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8870967741935484, "acc_stderr": 0.018003603325863593, "acc_norm": 0.8870967741935484, "acc_norm_stderr": 0.018003603325863593 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.6157635467980296, "acc_stderr": 0.034223985656575494, "acc_norm": 0.6157635467980296, "acc_norm_stderr": 0.034223985656575494 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.81, "acc_stderr": 0.03942772444036623, "acc_norm": 0.81, "acc_norm_stderr": 0.03942772444036623 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8727272727272727, "acc_stderr": 0.026024657651656187, "acc_norm": 0.8727272727272727, "acc_norm_stderr": 0.026024657651656187 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.9191919191919192, "acc_stderr": 0.019417681889724536, "acc_norm": 0.9191919191919192, "acc_norm_stderr": 0.019417681889724536 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9689119170984456, "acc_stderr": 0.012525310625527034, "acc_norm": 0.9689119170984456, "acc_norm_stderr": 0.012525310625527034 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.7974358974358975, "acc_stderr": 0.0203776609703714, "acc_norm": 0.7974358974358975, "acc_norm_stderr": 0.0203776609703714 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.37407407407407406, "acc_stderr": 0.029502861128955286, "acc_norm": 0.374074