open-llm-leaderboard-old/details_yys__gemma-7B-it-firefly

该数据集是在模型yys/gemma-7B-it-firefly在Open LLM Leaderboard上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。数据集包含一次运行的结果，每次运行都作为每个配置中的一个特定分割存储。train分割始终指向最新的结果。一个名为results的额外配置存储了所有运行的聚合结果，这些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Hugging Face datasets库加载数据集的示例。

原始信息汇总

数据集概述

数据集简介

该数据集是在模型 yys/gemma-7B-it-firefly 在 Open LLM Leaderboard 上的评估运行期间自动创建的。

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。
• 最新结果："train" 分割始终指向最新的结果。
• 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_yys__gemma-7B-it-firefly", "harness_winogrande_5", split="train")

最新结果

以下是 2024-03-27T21:35:16.393047 运行的最新结果：

python { "all": { "acc": 0.5274851026539407, "acc_stderr": 0.03426998317150207, "acc_norm": 0.5322216572588025, "acc_norm_stderr": 0.0349851498226043, "mc1": 0.2582619339045288, "mc1_stderr": 0.015321821688476189, "mc2": 0.42245555959891734, "mc2_stderr": 0.014963261529500903 }, "harness|arc:challenge|25": { "acc": 0.447098976109215, "acc_stderr": 0.014529380160526848, "acc_norm": 0.48293515358361777, "acc_norm_stderr": 0.014602878388536597 }, "harness|hellaswag|10": { "acc": 0.5315674168492333, "acc_stderr": 0.0049798268294007735, "acc_norm": 0.715893248356901, "acc_norm_stderr": 0.004500662294697923 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.27, "acc_stderr": 0.044619604333847394, "acc_norm": 0.27, "acc_norm_stderr": 0.044619604333847394 }, "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": 0.5328947368421053, "acc_stderr": 0.040601270352363966, "acc_norm": 0.5328947368421053, "acc_norm_stderr": 0.040601270352363966 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5886792452830188, "acc_stderr": 0.030285009259009784, "acc_norm": 0.5886792452830188, "acc_norm_stderr": 0.030285009259009784 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6041666666666666, "acc_stderr": 0.04089465449325582, "acc_norm": 0.6041666666666666, "acc_norm_stderr": 0.04089465449325582 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.41, "acc_stderr": 0.04943110704237102, "acc_norm": 0.41, "acc_norm_stderr": 0.04943110704237102 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.38, "acc_stderr": 0.04878317312145632, "acc_norm": 0.38, "acc_norm_stderr": 0.04878317312145632 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.35, "acc_stderr": 0.047937248544110196, "acc_norm": 0.35, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.49710982658959535, "acc_stderr": 0.038124005659748335, "acc_norm": 0.49710982658959535, "acc_norm_stderr": 0.038124005659748335 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.29411764705882354, "acc_stderr": 0.04533838195929775, "acc_norm": 0.29411764705882354, "acc_norm_stderr": 0.04533838195929775 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.46382978723404256, "acc_stderr": 0.03260038511835771, "acc_norm": 0.46382978723404256, "acc_norm_stderr": 0.03260038511835771 }, "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": 0.041657747757287644, "acc_norm": 0.4896551724137931, "acc_norm_stderr": 0.041657747757287644 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3544973544973545, "acc_stderr": 0.024636830602841997, "acc_norm": 0.3544973544973545, "acc_norm_stderr": 0.024636830602841997 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3968253968253968, "acc_stderr": 0.0437588849272706, "acc_norm": 0.3968253968253968, "acc_norm_stderr": 0.0437588849272706 }, "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": 0.6548387096774193, "acc_stderr": 0.027045746573534323, "acc_norm": 0.6548387096774193, "acc_norm_stderr": 0.027045746573534323 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.3891625615763547, "acc_stderr": 0.03430462416103872, "acc_norm": 0.3891625615763547, "acc_norm_stderr": 0.03430462416103872 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6363636363636364, "acc_stderr": 0.03756335775187897, "acc_norm": 0.6363636363636364, "acc_norm_stderr": 0.03756335775187897 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7171717171717171, "acc_stderr": 0.03208779558786751, "acc_norm": 0.7171717171717171, "acc_norm_stderr": 0.03208779558786751 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7150259067357513, "acc_stderr": 0.03257714077709662, "acc_norm": 0.7150259067357513, "acc_norm_stderr": 0.03257714077709662 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.49743589743589745, "acc_stderr": 0.025350672979412195, "acc_norm": 0.49743589743589745, "acc_norm_stderr": 0.025350672979412195 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3037037037037037, "acc_stderr": 0.028037929969114986, "acc_norm": 0.3037037