open-llm-leaderboard/details_xzuyn__LLaMa-2-LIMA-7B-QLoRA_v2

该数据集是在模型 xzuyn/LLaMa-2-LIMA-7B-QLoRA_v2 在 Open LLM Leaderboard 上的评估运行期间自动创建的。数据集由 61 个配置组成，每个配置对应一个评估任务。它由 1 次运行创建，每次运行在每个配置中作为特定的分割找到。train 分割始终指向最新的结果。一个额外的配置 results 存储了运行的所有聚合结果，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 库加载运行细节的示例。

原始信息汇总

数据集概述

数据集摘要

该数据集是在模型 xzuyn/LLaMa-2-LIMA-7B-QLoRA_v2 在 Open LLM Leaderboard 上的评估运行期间自动创建的。

数据集组成

• 数据集包含 61 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_xzuyn__LLaMa-2-LIMA-7B-QLoRA_v2", "harness_truthfulqa_mc_0", split="train")

最新结果

以下是 2023-08-29T20:43:19.802214 运行的最新结果： python { "all": { "acc": 0.42772147627937, "acc_stderr": 0.0352621795234267, "acc_norm": 0.43164590880132125, "acc_norm_stderr": 0.03524758282529255, "mc1": 0.28151774785801714, "mc1_stderr": 0.01574402724825605, "mc2": 0.42597374324834275, "mc2_stderr": 0.015781635062808143 }, "harness|arc:challenge|25": { "acc": 0.4880546075085324, "acc_stderr": 0.014607220340597171, "acc_norm": 0.5273037542662116, "acc_norm_stderr": 0.014589589101985994 }, "harness|hellaswag|10": { "acc": 0.6005775741884087, "acc_stderr": 0.004887787255353494, "acc_norm": 0.7928699462258514, "acc_norm_stderr": 0.004044213304049376 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.43703703703703706, "acc_stderr": 0.04284958639753399, "acc_norm": 0.43703703703703706, "acc_norm_stderr": 0.04284958639753399 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.4276315789473684, "acc_stderr": 0.04026097083296558, "acc_norm": 0.4276315789473684, "acc_norm_stderr": 0.04026097083296558 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.41509433962264153, "acc_stderr": 0.030325945789286105, "acc_norm": 0.41509433962264153, "acc_norm_stderr": 0.030325945789286105 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4583333333333333, "acc_stderr": 0.04166666666666665, "acc_norm": 0.4583333333333333, "acc_norm_stderr": 0.04166666666666665 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.28, "acc_stderr": 0.04512608598542128, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542128 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.3468208092485549, "acc_stderr": 0.036291466701596636, "acc_norm": 0.3468208092485549, "acc_norm_stderr": 0.036291466701596636 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.20588235294117646, "acc_stderr": 0.04023382273617747, "acc_norm": 0.20588235294117646, "acc_norm_stderr": 0.04023382273617747 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.39574468085106385, "acc_stderr": 0.03196758697835362, "acc_norm": 0.39574468085106385, "acc_norm_stderr": 0.03196758697835362 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.3333333333333333, "acc_stderr": 0.044346007015849245, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.044346007015849245 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.43448275862068964, "acc_stderr": 0.04130740879555497, "acc_norm": 0.43448275862068964, "acc_norm_stderr": 0.04130740879555497 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.2724867724867725, "acc_stderr": 0.02293097307163335, "acc_norm": 0.2724867724867725, "acc_norm_stderr": 0.02293097307163335 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.30158730158730157, "acc_stderr": 0.04104947269903394, "acc_norm": 0.30158730158730157, "acc_norm_stderr": 0.04104947269903394 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.43548387096774194, "acc_stderr": 0.028206225591502737, "acc_norm": 0.43548387096774194, "acc_norm_stderr": 0.028206225591502737 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.3645320197044335, "acc_stderr": 0.033864057460620905, "acc_norm": 0.3645320197044335, "acc_norm_stderr": 0.033864057460620905 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.5454545454545454, "acc_stderr": 0.038881769216741004, "acc_norm": 0.5454545454545454, "acc_norm_stderr": 0.038881769216741004 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.4898989898989899, "acc_stderr": 0.03561625488673745, "acc_norm": 0.4898989898989899, "acc_norm_stderr": 0.03561625488673745 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.6424870466321243, "acc_stderr": 0.03458816042181012, "acc_norm": 0.6424870466321243, "acc_norm_stderr": 0.03458816042181012 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.4128205128205128, "acc_stderr": 0.02496268356433182, "acc_norm": 0.4128205128205128, "acc_norm_stderr": 0.02496268356433182 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.25925925925925924, "acc_stderr": 0.026