open-llm-leaderboard-old/details_cloudyu__4bit_quant_TomGrc_FusionNet_34Bx2_MoE_v0.1_DPO

该数据集是在Open LLM Leaderboard上对特定模型进行评估时自动创建的。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1次运行创建，每次运行作为每个配置中的一个特定分割，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，还有一个名为results的配置，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。README还提供了一个使用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

数据集简介

该数据集是在模型cloudyu/4bit_quant_TomGrc_FusionNet_34Bx2_MoE_v0.1_DPO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"分割始终指向最新结果。
• 额外的"results"配置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_cloudyu__4bit_quant_TomGrc_FusionNet_34Bx2_MoE_v0.1_DPO", "harness_winogrande_5", split="train")

最新结果

以下是2024-02-03T11:35:18.964075运行的最新结果：

python { "all": { "acc": 0.7527363709875337, "acc_stderr": 0.028711415120135725, "acc_norm": 0.7558124417156407, "acc_norm_stderr": 0.029268003615455822, "mc1": 0.5630354957160343, "mc1_stderr": 0.017363844503195957, "mc2": 0.7277883751034597, "mc2_stderr": 0.014040395362394884 }, "harness|arc:challenge|25": { "acc": 0.7133105802047781, "acc_stderr": 0.013214986329274776, "acc_norm": 0.7320819112627986, "acc_norm_stderr": 0.01294203019513643 }, "harness|hellaswag|10": { "acc": 0.6624178450507867, "acc_stderr": 0.004719187890948062, "acc_norm": 0.8610834495120494, "acc_norm_stderr": 0.003451525868724678 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.51, "acc_stderr": 0.05024183937956913, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956913 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.7111111111111111, "acc_stderr": 0.03915450630414251, "acc_norm": 0.7111111111111111, "acc_norm_stderr": 0.03915450630414251 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.8552631578947368, "acc_stderr": 0.028631951845930387, "acc_norm": 0.8552631578947368, "acc_norm_stderr": 0.028631951845930387 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.77, "acc_stderr": 0.04229525846816505, "acc_norm": 0.77, "acc_norm_stderr": 0.04229525846816505 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7962264150943397, "acc_stderr": 0.024790784501775406, "acc_norm": 0.7962264150943397, "acc_norm_stderr": 0.024790784501775406 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8888888888888888, "acc_stderr": 0.026280550932848062, "acc_norm": 0.8888888888888888, "acc_norm_stderr": 0.026280550932848062 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.57, "acc_stderr": 0.04975698519562428, "acc_norm": 0.57, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.42, "acc_stderr": 0.04960449637488583, "acc_norm": 0.42, "acc_norm_stderr": 0.04960449637488583 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7456647398843931, "acc_stderr": 0.0332055644308557, "acc_norm": 0.7456647398843931, "acc_norm_stderr": 0.0332055644308557 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.5, "acc_stderr": 0.04975185951049946, "acc_norm": 0.5, "acc_norm_stderr": 0.04975185951049946 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.81, "acc_stderr": 0.039427724440366234, "acc_norm": 0.81, "acc_norm_stderr": 0.039427724440366234 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.7617021276595745, "acc_stderr": 0.02785125297388977, "acc_norm": 0.7617021276595745, "acc_norm_stderr": 0.02785125297388977 }, "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": 0.7034482758620689, "acc_stderr": 0.03806142687309992, "acc_norm": 0.7034482758620689, "acc_norm_stderr": 0.03806142687309992 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.6851851851851852, "acc_stderr": 0.023919984164047732, "acc_norm": 0.6851851851851852, "acc_norm_stderr": 0.023919984164047732 }, "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": 0.62, "acc_stderr": 0.04878317312145632, "acc_norm": 0.62, "acc_norm_stderr": 0.04878317312145632 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8774193548387097, "acc_stderr": 0.018656720991789413, "acc_norm": 0.8774193548387097, "acc_norm_stderr": 0.018656720991789413 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.6354679802955665, "acc_stderr": 0.0338640574606209, "acc_norm": 0.6354679802955665, "acc_norm_stderr": 0.0338640574606209 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.79, "acc_stderr": 0.040936018074033256, "acc_norm": 0.79, "acc_norm_stderr": 0.040936018074033256 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8545454545454545, "acc_stderr": 0.027530196355066584, "acc_norm": 0.8545454545454545, "acc_norm_stderr": 0.027530196355066584 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.9292929292929293, "acc_stderr": 0.018263105420199505, "acc_norm": 0.9292929292929293, "acc_norm_stderr": 0.018263105420199505 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9585492227979274, "acc_stderr": 0.014385432857476442, "acc_norm": 0.9585492227979274, "acc_norm_stderr": 0.014385432857476442 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.7794871794871795, "acc_stderr": 0.02102067268082791, "acc_norm": 0.7794871794871795, "acc_norm_stderr": 0.02102067268082791 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.45185185185185184, "acc_stderr": 0.030343862998512626, "acc_