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open-llm-leaderboard-old/details_yeontaek__llama-2-13B-ensemble-v5

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Hugging Face2023-08-29 更新2024-06-22 收录
下载链接:
https://hf-mirror.com/datasets/open-llm-leaderboard-old/details_yeontaek__llama-2-13B-ensemble-v5
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资源简介:
该数据集是在模型 yeontaek/llama-2-13B-ensemble-v5 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。数据集是从 1 次运行中创建的,每次运行在每个配置中作为一个特定的分割,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 代码加载运行中的详细信息的示例,并包含了特定运行的最新结果。

该数据集是在模型 yeontaek/llama-2-13B-ensemble-v5 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。数据集是从 1 次运行中创建的,每次运行在每个配置中作为一个特定的分割,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 代码加载运行中的详细信息的示例,并包含了特定运行的最新结果。
提供机构:
open-llm-leaderboard-old
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 yeontaek/llama-2-13B-ensemble-v5Open LLM Leaderboard 上的运行过程中自动创建的。

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。
  • 数据集由 1 次运行创建,每次运行可以在每个配置中找到特定的分片,分片名称使用运行的时间戳。
  • "train" 分片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_yeontaek__llama-2-13B-ensemble-v5", "harness_truthfulqa_mc_0", split="train")

最新结果

以下是 2023-08-29T09:17:14.183323 的最新结果:

python { "all": { "acc": 0.5953117661059801, "acc_stderr": 0.03391896483304526, "acc_norm": 0.5994365516843435, "acc_norm_stderr": 0.033896234769528244, "mc1": 0.3843329253365973, "mc1_stderr": 0.017028707301245203, "mc2": 0.5327328500103707, "mc2_stderr": 0.015551697577870274 }, "harness|arc:challenge|25": { "acc": 0.5844709897610921, "acc_stderr": 0.014401366641216388, "acc_norm": 0.6262798634812287, "acc_norm_stderr": 0.014137708601759084 }, "harness|hellaswag|10": { "acc": 0.6290579565823541, "acc_stderr": 0.004820697457420419, "acc_norm": 0.8306114319856602, "acc_norm_stderr": 0.0037432817493736324 }, "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": 0.5185185185185185, "acc_stderr": 0.043163785995113245, "acc_norm": 0.5185185185185185, "acc_norm_stderr": 0.043163785995113245 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.631578947368421, "acc_stderr": 0.03925523381052932, "acc_norm": 0.631578947368421, "acc_norm_stderr": 0.03925523381052932 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.59, "acc_stderr": 0.04943110704237102, "acc_norm": 0.59, "acc_norm_stderr": 0.04943110704237102 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6264150943396226, "acc_stderr": 0.029773082713319875, "acc_norm": 0.6264150943396226, "acc_norm_stderr": 0.029773082713319875 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6666666666666666, "acc_stderr": 0.03942082639927213, "acc_norm": 0.6666666666666666, "acc_norm_stderr": 0.03942082639927213 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.42, "acc_stderr": 0.04960449637488584, "acc_norm": 0.42, "acc_norm_stderr": 0.04960449637488584 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5722543352601156, "acc_stderr": 0.037724468575180255, "acc_norm": 0.5722543352601156, "acc_norm_stderr": 0.037724468575180255 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3627450980392157, "acc_stderr": 0.04784060704105653, "acc_norm": 0.3627450980392157, "acc_norm_stderr": 0.04784060704105653 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.68, "acc_stderr": 0.04688261722621505, "acc_norm": 0.68, "acc_norm_stderr": 0.04688261722621505 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.49361702127659574, "acc_stderr": 0.032683358999363366, "acc_norm": 0.49361702127659574, "acc_norm_stderr": 0.032683358999363366 }, "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": 0.5241379310344828, "acc_stderr": 0.0416180850350153, "acc_norm": 0.5241379310344828, "acc_norm_stderr": 0.0416180850350153 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.36243386243386244, "acc_stderr": 0.02475747390275206, "acc_norm": 0.36243386243386244, "acc_norm_stderr": 0.02475747390275206 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3968253968253968, "acc_stderr": 0.043758884927270605, "acc_norm": 0.3968253968253968, "acc_norm_stderr": 0.043758884927270605 }, "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": 0.6806451612903226, "acc_stderr": 0.026522709674667765, "acc_norm": 0.6806451612903226, "acc_norm_stderr": 0.026522709674667765 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4729064039408867, "acc_stderr": 0.03512819077876106, "acc_norm": 0.4729064039408867, "acc_norm_stderr": 0.03512819077876106 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.6, "acc_stderr": 0.04923659639173309, "acc_norm": 0.6, "acc_norm_stderr": 0.04923659639173309 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7212121212121212, "acc_stderr": 0.03501438706296781, "acc_norm": 0.7212121212121212, "acc_norm_stderr": 0.03501438706296781 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7676767676767676, "acc_stderr": 0.030088629490217487, "acc_norm": 0.7676767676767676, "acc_norm_stderr": 0.030088629490217487 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8756476683937824, "acc_stderr": 0.023814477086593552, "acc_norm": 0.8756476683937824, "acc_norm_stderr": 0.023814477086593552 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6076923076923076, "acc_stderr": 0.02475600038213095, "acc_norm": 0.6076923076923076, "acc_norm_stderr": 0.02475600038213095 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3333333333333333, "acc_stderr": 0.028742040903948496, "acc_norm": 0.

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