OALL/details_Mushari440__Qwen3-8B-SFT-V2_v2_alrage

---
pretty_name: Evaluation run of Mushari440/Qwen3-8B-SFT-V2
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [Mushari440/Qwen3-8B-SFT-V2](https://huggingface.co/Mushari440/Qwen3-8B-SFT-V2).\n\
\nThe dataset is composed of 1 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run.\n\nTo load the details from a run, you can for instance do the following:\n\
```python\nfrom datasets import load_dataset\ndata = load_dataset(\"OALL/details_Mushari440__Qwen3-8B-SFT-V2_v2_alrage\"\
,\n\t\"results\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\nThese are the\
\ [latest results from run 2026-03-02T21:15:57.176946](https://huggingface.co/datasets/OALL/details_Mushari440__Qwen3-8B-SFT-V2_v2_alrage/blob/main/results_2026-03-02T21-15-57.176946.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"llm_as_judge\": 0.34349477682810986,\n\
\ \"llm_as_judge_stderr\": 0.0001833679435819131\n },\n \"community|alrage_qa|0\"\
: {\n \"llm_as_judge\": 0.34349477682810986,\n \"llm_as_judge_stderr\"\
: 0.0001833679435819131\n }\n}\n```"
repo_url: https://huggingface.co/Mushari440/Qwen3-8B-SFT-V2
configs:
- config_name: community_alrage_qa_0
data_files:
- split: 2026_03_02T21_15_57.176946
path:
- '**/details_community|alrage_qa|0_2026-03-02T21-15-57.176946.parquet'
- split: latest
path:
- '**/details_community|alrage_qa|0_2026-03-02T21-15-57.176946.parquet'
- config_name: results
data_files:
- split: 2026_03_02T21_15_57.176946
path:
- results_2026-03-02T21-15-57.176946.parquet
- split: latest
path:
- results_2026-03-02T21-15-57.176946.parquet
---

# Dataset Card for Evaluation run of Mushari440/Qwen3-8B-SFT-V2

<!-- Provide a quick summary of the dataset. -->

Dataset automatically created during the evaluation run of model [Mushari440/Qwen3-8B-SFT-V2](https://huggingface.co/Mushari440/Qwen3-8B-SFT-V2).

The dataset is composed of 1 configuration, each one coresponding to one of the evaluated task.

The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.

An additional configuration "results" store all the aggregated results of the run.

To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("OALL/details_Mushari440__Qwen3-8B-SFT-V2_v2_alrage",
"results",
split="train")
```

## Latest results

These are the [latest results from run 2026-03-02T21:15:57.176946](https://huggingface.co/datasets/OALL/details_Mushari440__Qwen3-8B-SFT-V2_v2_alrage/blob/main/results_2026-03-02T21-15-57.176946.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):

```python
{
"all": {
"llm_as_judge": 0.34349477682810986,
"llm_as_judge_stderr": 0.0001833679435819131
},
"community|alrage_qa|0": {
"llm_as_judge": 0.34349477682810986,
"llm_as_judge_stderr": 0.0001833679435819131
}
}
```

## Dataset Details

### Dataset Description

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# Mushari440/Qwen3-8B-SFT-V2 模型评估运行数据集卡片

<!-- 简要描述本数据集。 -->

本数据集由模型[Mushari440/Qwen3-8B-SFT-V2](https://huggingface.co/Mushari440/Qwen3-8B-SFT-V2)的评估运行过程中自动生成。

本数据集包含1个配置项，每个配置项对应一项被评估的任务。

本数据集由1次运行生成。每次运行可通过各配置项下的特定拆分获取，拆分名称以运行的时间戳命名。其中"train"拆分始终指向最新的运行结果。

额外配置项"results"用于存储本次运行的所有聚合结果。

若要加载某次运行的详细数据，可参考如下示例代码：
python
from datasets import load_dataset
data = load_dataset("OALL/details_Mushari440__Qwen3-8B-SFT-V2_v2_alrage",
"results",
split="train")

## 最新结果

以下为来自[2026-03-02T21:15:57.176946运行的结果](https://huggingface.co/datasets/OALL/details_Mushari440__Qwen3-8B-SFT-V2_v2_alrage/blob/main/results_2026-03-02T21-15-57.176946.json)（注：若连续两次评估未覆盖相同任务，则仓库中可能存在其他任务的结果。您可在各评估的结果文件与对应评估的"latest"拆分中找到所需内容）：

python
{
"all": {
"llm_as_judge": 0.34349477682810986,
"llm_as_judge_stderr": 0.0001833679435819131
},
"community|alrage_qa|0": {
"llm_as_judge": 0.34349477682810986,
"llm_as_judge_stderr": 0.0001833679435819131
}
}

## 数据集基本信息

- 展示名称：Mushari440/Qwen3-8B-SFT-V2 模型评估运行数据集
- 数据集摘要：本数据集由模型[Mushari440/Qwen3-8B-SFT-V2](https://huggingface.co/Mushari440/Qwen3-8B-SFT-V2)的评估运行过程中自动生成。本数据集包含1个配置项，每个配置项对应一项被评估的任务。本数据集由1次运行生成，每次运行可通过各配置项下的特定拆分获取，拆分名称以运行的时间戳命名，其中"train"拆分始终指向最新的运行结果。额外配置项"results"用于存储本次运行的所有聚合结果。
- 仓库链接：https://huggingface.co/Mushari440/Qwen3-8B-SFT-V2
- 配置项：
1. 配置名称：community_alrage_qa_0
数据文件：
- 拆分：2026_03_02T21_15_57.176946
路径：`['**/details_community|alrage_qa|0_2026-03-02T21-15-57.176946.parquet']`
- 拆分：latest
路径：`['**/details_community|alrage_qa|0_2026-03-02T21-15-57.176946.parquet']`
2. 配置名称：results
数据文件：
- 拆分：2026_03_02T21_15_57.176946
路径：`['results_2026-03-02T21-15-57.176946.parquet']`
- 拆分：latest
路径：`['results_2026-03-02T21-15-57.176946.parquet']`

## 数据集详情

### 数据集描述

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用户应知晓本数据集存在的风险、偏差与局限性。需补充更多信息以提供进一步建议。

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