open-llm-leaderboard-old/details_one-man-army__UNA-34Beagles-32K-bf16-v1
收藏数据集概述
该数据集是在评估模型one-man-army/UNA-34Beagles-32K-bf16-v1在Open LLM Leaderboard上的自动创建的。数据集包含63个配置,每个配置对应一个评估任务。
数据集结构
- 配置数量:63个配置
- 数据来源:1次运行(run),每个运行在每个配置中作为一个特定的分割(split),分割名称使用运行的时间戳。
- 最新结果:"train"分割总是指向最新的结果。
- 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_one-man-army__UNA-34Beagles-32K-bf16-v1", "harness_winogrande_5", split="train")
最新结果
以下是2024-01-14T18:01:24.840782运行的最新结果:
python { "all": { "acc": 0.7603825099190668, "acc_stderr": 0.028403734149400593, "acc_norm": 0.7656218376316938, "acc_norm_stderr": 0.02893068310994367, "mc1": 0.5887392900856793, "mc1_stderr": 0.01722562708366087, "mc2": 0.7354905615781797, "mc2_stderr": 0.014104277111112697 }, "harness|arc:challenge|25": { "acc": 0.7047781569965871, "acc_stderr": 0.01332975029338232, "acc_norm": 0.735494880546075, "acc_norm_stderr": 0.012889272949313368 }, "harness|hellaswag|10": { "acc": 0.6716789484166501, "acc_stderr": 0.004686425851253278, "acc_norm": 0.85929097789285, "acc_norm_stderr": 0.00347010499020439 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.49, "acc_stderr": 0.05024183937956911, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956911 }, ... }
配置详情
-
harness_arc_challenge_25
- 分割:2024_01_14T18_01_24.840782, latest
- 路径:
**/details_harness|arc:challenge|25_2024-01-14T18-01-24.840782.parquet
-
harness_gsm8k_5
- 分割:2024_01_14T18_01_24.840782, latest
- 路径:
**/details_harness|gsm8k|5_2024-01-14T18-01-24.840782.parquet
-
harness_hellaswag_10
- 分割:2024_01_14T18_01_24.840782, latest
- 路径:
**/details_harness|hellaswag|10_2024-01-14T18-01-24.840782.parquet
-
harness_hendrycksTest_5
- 分割:2024_01_14T18_01_24.840782, latest
- 路径:多个路径,包括
**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-14T18-01-24.840782.parquet等



