lm-eval-EleutherAI_deep-ignorance-random-init

# Dataset Card for Evaluation run of EleutherAI/deep-ignorance-random-init

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

Dataset automatically created during the evaluation run of model [EleutherAI/deep-ignorance-random-init](https://huggingface.co/EleutherAI/deep-ignorance-random-init)
The dataset is composed of 0 configuration(s), each one corresponding 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(
"EleutherAI/lm-eval-EleutherAI_deep-ignorance-random-init",
name="EleutherAI__deep-ignorance-random-init__wmdp_bio_aisi_cloze_verified",
split="latest"
)
```

## Latest results

These are the [latest results from run 2025-11-04T19-08-13.108477](https://huggingface.co/datasets/EleutherAI/lm-eval-EleutherAI_deep-ignorance-random-init/blob/main/EleutherAI/deep-ignorance-random-init/results_2025-11-04T19-08-13.108477.json) (note that there 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": {
"wmdp_bio_aisi_cloze_verified": {
"alias": "wmdp_bio_aisi_cloze_verified",
"acc_norm,none": 0.25,
"acc_norm_stderr,none": 0.013206763594884355
}
},
"wmdp_bio_aisi_cloze_verified": {
"alias": "wmdp_bio_aisi_cloze_verified",
"acc_norm,none": 0.25,
"acc_norm_stderr,none": 0.013206763594884355
}
}
```

## 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]

<!-- Provide the basic links for the dataset. -->

- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]

## Uses

<!-- Address questions around how the dataset is intended to be used. -->

### Direct Use

<!-- This section describes suitable use cases for the dataset. -->

[More Information Needed]

### Out-of-Scope Use

<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->

[More Information Needed]

## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->

[More Information Needed]

## Dataset Creation

### Curation Rationale

<!-- Motivation for the creation of this dataset. -->

[More Information Needed]

### Source Data

<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->

#### Data Collection and Processing

<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->

[More Information Needed]

#### Who are the source data producers?

<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->

[More Information Needed]

### Annotations [optional]

<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->

#### Annotation process

<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->

[More Information Needed]

#### Who are the annotators?

<!-- This section describes the people or systems who created the annotations. -->

[More Information Needed]

#### Personal and Sensitive Information

<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->

[More Information Needed]

## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

[More Information Needed]

### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

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

## Citation [optional]

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

[More Information Needed]

**APA:**

[More Information Needed]

## Glossary [optional]

<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->

[More Information Needed]

## More Information [optional]

[More Information Needed]

## Dataset Card Authors [optional]

[More Information Needed]

## Dataset Card Contact

[More Information Needed]

# EleutherAI/deep-ignorance-random-init 评估运行数据集卡片（Dataset Card）

<!-- 提供该数据集的快速概述。 -->

本数据集为模型[EleutherAI/deep-ignorance-random-init](https://huggingface.co/EleutherAI/deep-ignorance-random-init)的评估运行期间自动生成的数据集。该数据集包含0个配置项，每个配置项对应一项被评估的任务。

本数据集基于2次运行结果构建而成。每次运行的结果会作为对应配置下的特定拆分（split），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评估结果。

此外还存在一个额外的"results"配置项，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(
"EleutherAI/lm-eval-EleutherAI_deep-ignorance-random-init",
name="EleutherAI__deep-ignorance-random-init__wmdp_bio_aisi_cloze_verified",
split="latest"
)

## 最新评估结果

以下为[2025-11-04T19-08-13.108477运行的最新结果](https://huggingface.co/datasets/EleutherAI/lm-eval-EleutherAI_deep-ignorance-random-init/blob/main/EleutherAI/deep-ignorance-random-init/results_2025-11-04T19-08-13.108477.json)（请注意：若后续的评估未覆盖全部任务，则仓库中可能存在其他任务的评估结果。你可以在各评估的"results"与对应评估的"latest"拆分中找到所有结果）：

python
{
"all": {
"wmdp_bio_aisi_cloze_verified": {
"alias": "wmdp_bio_aisi_cloze_verified",
"acc_norm,none": 0.25,
"acc_norm_stderr,none": 0.013206763594884355
}
},
"wmdp_bio_aisi_cloze_verified": {
"alias": "wmdp_bio_aisi_cloze_verified",
"acc_norm,none": 0.25,
"acc_norm_stderr,none": 0.013206763594884355
}
}

## 数据集详情

### 数据集概述

<!-- 提供该数据集的详细概述。 -->

- **整理者：** [需补充更多信息]
- **资助方（可选）：** [需补充更多信息]
- **分享方（可选）：** [需补充更多信息]
- **自然语言（NLP）：** [需补充更多信息]
- **许可证：** [需补充更多信息]

### 数据集来源（可选）

<!-- 提供该数据集的基础链接信息。 -->

- **代码仓库：** [需补充更多信息]
- **相关论文（可选）：** [需补充更多信息]
- **演示示例（可选）：** [需补充更多信息]

## 用途

<!-- 说明该数据集的预期使用场景相关问题。 -->

### 直接使用场景

<!-- 本部分描述该数据集适配的使用场景。 -->

[需补充更多信息]

### 超出范围的使用场景

<!-- 本部分说明不当使用、恶意使用，以及该数据集无法适配的使用场景。 -->

[需补充更多信息]

## 数据集结构

<!-- 本部分描述数据集的字段信息，以及额外的数据集结构相关细节，例如拆分创建的标准、数据点间的关联关系等。 -->

[需补充更多信息]

## 数据集创建

### 整理初衷

<!-- 本部分说明创建该数据集的动机。 -->

[需补充更多信息]

### 源数据

<!-- 本部分描述源数据的相关信息（例如新闻文本与标题、社交媒体帖文、翻译语句等）。 -->

#### 数据收集与处理流程

<!-- 本部分说明数据收集与处理的过程，例如数据选择标准、过滤与归一化方法、使用的工具与库等。 -->

[需补充更多信息]

#### 源数据生产者是谁？

<!-- 本部分描述最初创建该数据的个人或系统。若可获取源数据创建者的自我报告式人口统计或身份信息，也应在此处说明。 -->

[需补充更多信息]

### 标注信息（可选）

<!-- 若数据集包含初始数据收集之外的标注内容，请在此部分描述相关信息。 -->

#### 标注流程

<!-- 本部分说明标注流程，例如标注过程中使用的工具、标注数据量、提供给标注者的标注指南、标注者间一致性统计、标注验证方式等。 -->

[需补充更多信息]

#### 标注者是谁？

<!-- 本部分描述创建标注内容的个人或系统。 -->

[需补充更多信息]

#### 个人与敏感信息

<!-- 说明该数据集是否包含可被视为个人、敏感或私密的数据（例如：披露地址、唯一可识别的姓名或别名、种族或族裔出身、性取向、宗教信仰、政治观点、财务或健康数据等）。若曾对数据进行匿名化处理，请说明匿名化流程。 -->

[需补充更多信息]

## 偏差、风险与局限性

<!-- 本部分旨在说明技术与社会技术层面的局限性。 -->

[需补充更多信息]

### 建议

<!-- 本部分旨在针对数据集的偏差、风险与技术局限性给出相关建议。 -->

用户应知晓该数据集存在的风险、偏差与局限性。如需进一步的建议，需补充更多相关信息。

## 引用信息（可选）

<!-- 若存在介绍该数据集的论文或博客文章，此处应包含其APA与BibTeX格式的引用信息。 -->

**BibTeX格式：**

[需补充更多信息]

**APA格式：**

[需补充更多信息]

## 术语表（可选）

<!-- 若有需要，可在此部分添加可帮助读者理解数据集或数据集卡片的术语与计算公式。 -->

[需补充更多信息]

## 更多信息（可选）

[需补充更多信息]

## 数据集卡片作者（可选）

[需补充更多信息]

## 数据集卡片联系人

[需补充更多信息]