Beratcam06/datasetsss

---
# For reference on dataset card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1
# Doc / guide: https://huggingface.co/docs/hub/datasets-cards
{"annotations_creators:
- expert-generated
language_creators:
- found
language:
- zh
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
paperswithcode_id: nlp-model-tune
pretty_name: NER Model Tune
train-eval-index:
- config: default
task: token-classification
task_id: entity_extraction
splits:
train_split: train
eval_split: test
col_mapping:
tokens: tokens
ner_tags: tags
metrics:
- type: seqeval
name: seqeval
dataset_info:
features:
- name: id
dtype: string
- name: tokens
sequence: string
- name: ner_tags
sequence:
class_label:
names:
'0': O,
'1': B-ANAT,
'2': I-ANAT,
splits:
- name: train
num_bytes: 568
num_examples: 1
download_size: 568
dataset_size: 568"}
---

# Dataset Card for Dataset Name

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

This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).

## 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]

# 参考数据集卡片元数据规范，请参阅：https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1
# 文档/指南：https://huggingface.co/docs/hub/datasets-cards
---
annotations_creators: 专家生成
language_creators: 采集所得
language: zh
license: 未知
multilinguality: 单语言
size_categories: 1K<n<10K
source_datasets: 原始数据集
task_categories: 词元（Token）分类
task_ids: 命名实体识别（Named Entity Recognition）
paperswithcode_id: nlp-model-tune
pretty_name: NER模型调优
train-eval-index:
- config: 默认配置
task: 词元（Token）分类
task_id: 实体抽取
splits:
train_split: 训练集
eval_split: 测试集
col_mapping:
tokens: 词元序列
ner_tags: 命名实体标签
metrics:
- type: seqeval
name: seqeval
dataset_info:
features:
- name: id
dtype: 字符串
- name: tokens
sequence: 字符串
- name: ner_tags
sequence:
class_label:
names:
'0': O
'1': B-ANAT
'2': I-ANAT
splits:
- name: train
num_bytes: 568
num_examples: 1
download_size: 568
dataset_size: 568
---

# 数据集卡片
<!-- 提供数据集的简要摘要。 -->
本数据集卡片旨在作为新数据集的基础模板。本卡片通过[此原始模板](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1)生成。

## 数据集详情
### 数据集描述
<!-- 提供该数据集的详细摘要。 -->

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

### 数据集来源（可选）
<!-- 提供数据集的基础链接。 -->
- **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]

## 数据集用途
<!-- 讨论该数据集的预期使用场景相关问题。 -->
### 直接使用
<!-- 本节描述该数据集的适用用例。 -->
[需补充更多信息]

### 超出范围的使用
<!-- 本节讨论误用、恶意使用，以及该数据集无法良好适配的使用场景。 -->
[需补充更多信息]

## 数据集结构
<!-- 本节描述数据集的字段信息，以及额外的数据集结构相关信息，例如数据拆分的创建标准、数据点间的关联关系等。 -->
[需补充更多信息]

## 数据集创建
### 整理依据
<!-- 创建该数据集的动机。 -->
[需补充更多信息]

### 源数据
<!-- 本节描述源数据（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
<!-- 本节描述数据收集与处理流程，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？
<!-- 本节描述最初创建该数据的个人或系统。若有可用的源数据创建者的自我报告人口统计或身份信息，也应在此处包含。 -->
[需补充更多信息]

### 标注（可选）
<!-- 若数据集包含非初始数据收集阶段生成的标注，请使用本节描述相关信息。 -->
#### 标注流程
<!-- 本节描述标注流程，例如过程中使用的标注工具、已标注的数据量、向标注者提供的标注指南、标注者间统计数据、标注验证等。 -->
[需补充更多信息]

#### 标注者是谁？
<!-- 本节描述创建标注的个人或系统。 -->
[需补充更多信息]

#### 个人与敏感信息
<!-- 说明数据集是否包含可被视为个人、敏感或私密的数据（例如：泄露地址、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）。若已采取措施对数据进行匿名化，请描述匿名化流程。 -->
[需补充更多信息]

## 偏差、风险与局限性
<!-- 本节旨在传达技术与社会技术层面的局限性。 -->
### 建议
<!-- 本节旨在就数据集的偏差、风险与技术局限性给出建议。 -->
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，还需补充更多信息。

## 引用（可选）
<!-- 若有介绍该数据集的论文或博客文章，应在此处给出其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，可在本节包含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]

原始信息汇总

数据集卡片

数据集详情

数据集描述

• 语言(s) (NLP): 中文
• 许可证: 未知
• 多语言性: 单语种
• 大小类别: 1K<n<10K
• 源数据集: 原始数据集
• 任务类别: 标记分类
• 任务ID: 命名实体识别
• paperswithcode ID: nlp-model-tune
• 美观名称: NER Model Tune

训练与评估索引

• 配置: 默认
• 任务: 标记分类
• 任务ID: 实体提取
• 分割:
  • 训练分割: 训练
  • 评估分割: 测试
• 列映射:
  • tokens: tokens
  • ner_tags: tags
• 指标:
  • 类型: seqeval
  • 名称: seqeval

数据集信息

• 特征:
  • 名称: id
    • 数据类型: 字符串
  • 名称: tokens
    • 序列: 字符串
  • 名称: ner_tags
    • 序列:
      • 类标签:
        • 名称:
          • 0: O
          • 1: B-ANAT
          • 2: I-ANAT
• 分割:
  • 名称: 训练
    • 字节数: 568
    • 示例数: 1
• 下载大小: 568
• 数据集大小: 568