OALL/details_Mushari440__qwen3-8B-SFT_v2_alrage

---
pretty_name: Evaluation run of Mushari440/qwen3-8B-SFT
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [Mushari440/qwen3-8B-SFT](https://huggingface.co/Mushari440/qwen3-8B-SFT).\n\n\
The dataset is composed of 1 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 2 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_alrage\"\
,\n\t\"results\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\nThese are the\
\ [latest results from run 2026-02-23T17:54:00.359240](https://huggingface.co/datasets/OALL/details_Mushari440__qwen3-8B-SFT_v2_alrage/blob/main/results_2026-02-23T17-54-00.359240.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\": 0.6788224121557429,\n\
\ \"llm_as_judge_stderr\": 0.00017077427346600052\n },\n \"community|alrage_qa|0\"\
: {\n \"llm_as_judge\": 0.6788224121557429,\n \"llm_as_judge_stderr\"\
: 0.00017077427346600052\n }\n}\n```"
repo_url: https://huggingface.co/Mushari440/qwen3-8B-SFT
configs:
- config_name: community_alrage_qa_0
data_files:
- split: 2026_02_14T13_26_34.483657
path:
- '**/details_community|alrage_qa|0_2026-02-14T13-26-34.483657.parquet'
- split: 2026_02_23T17_54_00.359240
path:
- '**/details_community|alrage_qa|0_2026-02-23T17-54-00.359240.parquet'
- split: latest
path:
- '**/details_community|alrage_qa|0_2026-02-23T17-54-00.359240.parquet'
- config_name: results
data_files:
- split: 2026_02_14T13_26_34.483657
path:
- results_2026-02-14T13-26-34.483657.parquet
- split: 2026_02_23T17_54_00.359240
path:
- results_2026-02-23T17-54-00.359240.parquet
- split: latest
path:
- results_2026-02-23T17-54-00.359240.parquet
---

# Dataset Card for Evaluation run of Mushari440/qwen3-8B-SFT

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

Dataset automatically created during the evaluation run of model [Mushari440/qwen3-8B-SFT](https://huggingface.co/Mushari440/qwen3-8B-SFT).

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

The dataset has been created from 2 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_alrage",
"results",
split="train")
```

## Latest results

These are the [latest results from run 2026-02-23T17:54:00.359240](https://huggingface.co/datasets/OALL/details_Mushari440__qwen3-8B-SFT_v2_alrage/blob/main/results_2026-02-23T17-54-00.359240.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": 0.6788224121557429,
"llm_as_judge_stderr": 0.00017077427346600052
},
"community|alrage_qa|0": {
"llm_as_judge": 0.6788224121557429,
"llm_as_judge_stderr": 0.00017077427346600052
}
}
```

## Dataset Details

### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->

- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]

### Dataset Sources [optional]

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- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
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## Uses

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### Direct Use

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### Out-of-Scope Use

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## Dataset Structure

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## Dataset Creation

### Curation Rationale

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### Source Data

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#### Data Collection and Processing

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#### Who are the source data producers?

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### Annotations [optional]

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#### Annotation process

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#### Who are the annotators?

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#### Personal and Sensitive Information

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[More Information Needed]

## Bias, Risks, and Limitations

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[More Information Needed]

### Recommendations

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Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

## Citation [optional]

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**BibTeX:**

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## Glossary [optional]

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pretty_name: "Mushari440/qwen3-8B-SFT 模型评估运行数据集"
dataset_summary: "本数据集由模型[Mushari440/qwen3-8B-SFT](https://huggingface.co/Mushari440/qwen3-8B-SFT)的评估运行过程中自动生成。

本数据集包含1个配置项，每个配置项对应一个评估任务。

本数据集基于2次评估运行生成。每次运行均可在各配置项中以特定拆分（split）形式找到，拆分名称采用运行的时间戳命名。其中"train"拆分始终指向最新的评估结果。

额外配置项"results"用于存储本次评估运行的所有聚合结果。

若需加载某次运行的详细信息，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_alrage",
"results",
split="train")

## 最新评估结果

以下为2026年2月23日17:54:00.359240运行的最新结果[点击查看](https://huggingface.co/datasets/OALL/details_Mushari440__qwen3-8B-SFT_v2_alrage/blob/main/results_2026-02-23T17-54-00.359240.json)（注：若连续多次评估未覆盖全部任务，则仓库中可能存在其他任务的结果，各任务的结果与对应评估的"latest"拆分均可在结果文件中找到）：

python
{
"all": {
"llm_as_judge": 0.6788224121557429,
"llm_as_judge_stderr": 0.00017077427346600052
},
"community|alrage_qa|0": {
"llm_as_judge": 0.6788224121557429,
"llm_as_judge_stderr": 0.00017077427346600052
}
}

repo_url: https://huggingface.co/Mushari440/qwen3-8B-SFT
configs:
- config_name: community_alrage_qa_0
data_files:
- split: 2026_02_14T13_26_34.483657
path:
- '**/details_community|alrage_qa|0_2026-02-14T13-26-34.483657.parquet'
- split: 2026_02_23T17_54_00.359240
path:
- '**/details_community|alrage_qa|0_2026-02-23T17-54-00.359240.parquet'
- split: latest
path:
- '**/details_community|alrage_qa|0_2026-02-23T17-54-00.359240.parquet'
- config_name: results
data_files:
- split: 2026_02_14T13_26_34.483657
path:
- results_2026-02-14T13-26-34.483657.parquet
- split: 2026_02_23T17_54_00.359240
path:
- results_2026-02-23T17-54-00.359240.parquet
- split: latest
path:
- results_2026-02-23T17-54-00.359240.parquet

---

# Mushari440/qwen3-8B-SFT 模型评估运行数据集卡片

<!-- 请简要概述本数据集。 -->

本数据集由模型[Mushari440/qwen3-8B-SFT](https://huggingface.co/Mushari440/qwen3-8B-SFT)的评估运行过程中自动生成。

本数据集包含1个配置项，每个配置项对应一个评估任务。

本数据集基于2次评估运行生成。每次运行均可在各配置项中以特定拆分（split）形式找到，拆分名称采用运行的时间戳命名。其中"train"拆分始终指向最新的评估结果。

额外配置项"results"用于存储本次评估运行的所有聚合结果。

若需加载某次运行的详细信息，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_alrage",
"results",
split="train")

## 最新评估结果

以下为2026年2月23日17:54:00.359240运行的最新结果[点击查看](https://huggingface.co/datasets/OALL/details_Mushari440__qwen3-8B-SFT_v2_alrage/blob/main/results_2026-02-23T17-54-00.359240.json)（注：若连续多次评估未覆盖全部任务，则仓库中可能存在其他任务的结果，各任务的结果与对应评估的"latest"拆分均可在结果文件中找到）：

python
{
"all": {
"llm_as_judge": 0.6788224121557429,
"llm_as_judge_stderr": 0.00017077427346600052
},
"community|alrage_qa|0": {
"llm_as_judge": 0.6788224121557429,
"llm_as_judge_stderr": 0.00017077427346600052
}
}

## 数据集详情

### 数据集描述

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## 数据集用途

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[需补充更多信息]

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## 数据集结构

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## 数据集构建

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[需补充更多信息]

#### 标注人员

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#### 个人与敏感信息

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## 偏差、风险与局限性

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### 建议

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

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## 数据集卡片联系人

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