plaguss/ag_news_tutorial

---
size_categories: 1K<n<10K
tags:
- rlfh
- argilla
- human-feedback
---

# Dataset Card for ag_news_tutorial

This dataset has been created with [Argilla](https://docs.argilla.io).

As shown in the sections below, this dataset can be loaded into Argilla as explained in [Load with Argilla](#load-with-argilla), or used directly with the `datasets` library in [Load with `datasets`](#load-with-datasets).

## Dataset Description

- **Homepage:** https://argilla.io
- **Repository:** https://github.com/argilla-io/argilla
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**

### Dataset Summary

This dataset contains:

* A dataset configuration file conforming to the Argilla dataset format named `argilla.yaml`. This configuration file will be used to configure the dataset when using the `FeedbackDataset.from_huggingface` method in Argilla.

* Dataset records in a format compatible with HuggingFace `datasets`. These records will be loaded automatically when using `FeedbackDataset.from_huggingface` and can be loaded independently using the `datasets` library via `load_dataset`.

* The [annotation guidelines](#annotation-guidelines) that have been used for building and curating the dataset, if they've been defined in Argilla.

### Load with Argilla

To load with Argilla, you'll just need to install Argilla as `pip install argilla --upgrade` and then use the following code:

```python
import argilla as rg

ds = rg.FeedbackDataset.from_huggingface("plaguss/ag_news_tutorial")
```

### Load with `datasets`

To load this dataset with `datasets`, you'll just need to install `datasets` as `pip install datasets --upgrade` and then use the following code:

```python
from datasets import load_dataset

ds = load_dataset("plaguss/ag_news_tutorial")
```

### Supported Tasks and Leaderboards

This dataset can contain [multiple fields, questions and responses](https://docs.argilla.io/en/latest/conceptual_guides/data_model.html#feedback-dataset) so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the [Dataset Structure section](#dataset-structure).

There are no leaderboards associated with this dataset.

### Languages

[More Information Needed]

## Dataset Structure

### Data in Argilla

The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, **metadata**, and **guidelines**.

The **fields** are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.

| Field Name | Title | Type | Required | Markdown |
| ---------- | ----- | ---- | -------- | -------- |
| text | Text from the article | text | True | False |

The **questions** are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label_selection, multi_label_selection, or ranking.

| Question Name | Title | Type | Required | Description | Values/Labels |
| ------------- | ----- | ---- | -------- | ----------- | ------------- |
| label | In which category does this article fit? | label_selection | True | N/A | ['0', '1', '2', '3'] |

The **suggestions** are human or machine generated recommendations for each question to assist the annotator during the annotation process, so those are always linked to the existing questions, and named appending "-suggestion" and "-suggestion-metadata" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above, but the column name is appended with "-suggestion" and the metadata is appended with "-suggestion-metadata".

**✨ NEW** The **metadata** is a dictionary that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the `metadata_properties` defined in the dataset configuration file in `argilla.yaml`.

The **guidelines**, are optional as well, and are just a plain string that can be used to provide instructions to the annotators. Find those in the [annotation guidelines](#annotation-guidelines) section.

### Data Instances

An example of a dataset instance in Argilla looks as follows:

```json
{
"external_id": "record-0",
"fields": {
"text": "Wall St. Bears Claw Back Into the Black (Reuters) Reuters - Short-sellers, Wall Street\u0027s dwindling\\band of ultra-cynics, are seeing green again."
},
"metadata": {},
"responses": [],
"suggestions": []
}
```

While the same record in HuggingFace `datasets` looks as follows:

```json
{
"external_id": "record-0",
"label": [],
"label-suggestion": null,
"label-suggestion-metadata": {
"agent": null,
"score": null,
"type": null
},
"metadata": "{}",
"text": "Wall St. Bears Claw Back Into the Black (Reuters) Reuters - Short-sellers, Wall Street\u0027s dwindling\\band of ultra-cynics, are seeing green again."
}
```

### Data Fields

Among the dataset fields, we differentiate between the following:

* **Fields:** These are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.

* **text** is of type `text`.

* **Questions:** These are the questions that will be asked to the annotators. They can be of different types, such as `RatingQuestion`, `TextQuestion`, `LabelQuestion`, `MultiLabelQuestion`, and `RankingQuestion`.

* **label** is of type `label_selection` with the following allowed values ['0', '1', '2', '3'].

* **Suggestions:** As of Argilla 1.13.0, the suggestions have been included to provide the annotators with suggestions to ease or assist during the annotation process. Suggestions are linked to the existing questions, are always optional, and contain not just the suggestion itself, but also the metadata linked to it, if applicable.

* (optional) **label-suggestion** is of type `label_selection` with the following allowed values ['0', '1', '2', '3'].

Additionally, we also have two more fields that are optional and are the following:

* **✨ NEW** **metadata:** This is an optional field that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the `metadata_properties` defined in the dataset configuration file in `argilla.yaml`.
* **external_id:** This is an optional field that can be used to provide an external ID for the dataset record. This can be useful if you want to link the dataset record to an external resource, such as a database or a file.

### Data Splits

The dataset contains a single split, which is `train`.

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation guidelines

This dataset contains a collection of news articles. Please label them on the category they belong.

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### Citation Information

[More Information Needed]

### Contributions

[More Information Needed]

原始信息汇总

数据集卡片 for ag_news_tutorial

数据集描述

• 主页: https://argilla.io
• 仓库: https://github.com/argilla-io/argilla
• 论文:
• 排行榜:
• 联系人:

数据集概述

该数据集包含：

• 符合 Argilla 数据集格式的配置文件 argilla.yaml。该配置文件将在使用 Argilla 的 FeedbackDataset.from_huggingface 方法时用于配置数据集。
• 与 HuggingFace datasets 兼容的数据集记录。这些记录在使用 FeedbackDataset.from_huggingface 时会自动加载，也可以通过 datasets 库的 load_dataset 方法独立加载。
• 用于构建和整理数据集的标注指南（如果已在 Argilla 中定义）。

加载方式

使用 Argilla 加载

安装 Argilla：

python pip install argilla --upgrade

然后使用以下代码加载数据集：

python import argilla as rg

ds = rg.FeedbackDataset.from_huggingface("plaguss/ag_news_tutorial")

使用 datasets 加载

安装 datasets：

python pip install datasets --upgrade

然后使用以下代码加载数据集：

python from datasets import load_dataset

ds = load_dataset("plaguss/ag_news_tutorial")

支持的任务和排行榜

该数据集可以包含多个字段、问题和响应，因此可以用于不同的 NLP 任务，具体取决于配置。数据集结构在数据集结构部分中描述。

该数据集没有关联的排行榜。

语言

[更多信息待补充]

数据集结构

数据在 Argilla 中

数据集在 Argilla 中创建，包含以下内容：字段、问题、建议、元数据和指南。

字段是数据集记录本身，目前仅支持文本字段。这些字段将用于提供问题的答案。

字段名称	标题	类型	必需	Markdown
text	文章文本	text	True	False

问题是向标注者提出的问题。它们可以是不同类型，如评分、文本、标签选择、多标签选择或排序。

问题名称	标题	类型	必需	描述	值/标签
label	这篇文章属于哪个类别？	label_selection	True	N/A	[0, 1, 2, 3]

建议是人为或机器生成的推荐，用于在标注过程中协助标注者。建议始终与现有问题相关联，并命名为“-suggestion”和“-suggestion-metadata”，包含建议的值及其元数据。

✨ NEW 元数据是一个字典，用于提供有关数据集记录的额外信息。这可以为标注者提供额外的上下文，或提供有关数据集记录本身的额外信息。元数据始终是可选的，并且可以与 argilla.yaml 中的 metadata_properties 定义相关联。

指南是可选的，只是一个用于向标注者提供指令的纯字符串。请参阅标注指南部分。

数据实例

在 Argilla 中的数据集实例示例如下：

json { "external_id": "record-0", "fields": { "text": "Wall St. Bears Claw Back Into the Black (Reuters) Reuters - Short-sellers, Wall Streetu0027s dwindling\band of ultra-cynics, are seeing green again." }, "metadata": {}, "responses": [], "suggestions": [] }

在 HuggingFace datasets 中的相同记录示例如下：

json { "external_id": "record-0", "label": [], "label-suggestion": null, "label-suggestion-metadata": { "agent": null, "score": null, "type": null }, "metadata": "{}", "text": "Wall St. Bears Claw Back Into the Black (Reuters) Reuters - Short-sellers, Wall Streetu0027s dwindling\band of ultra-cynics, are seeing green again." }

数据字段

数据集字段包括以下内容：

• 字段： 这些是数据集记录本身，目前仅支持文本字段。这些字段将用于提供问题的答案。

  • text 是 text 类型。

• 问题： 这些是向标注者提出的问题。它们可以是不同类型，如 RatingQuestion、TextQuestion、LabelQuestion、MultiLabelQuestion 和 RankingQuestion。

  • label 是 label_selection 类型，允许的值为 [0, 1, 2, 3]。

• 建议： 从 Argilla 1.13.0 开始，建议已包含在内，以在标注过程中为标注者提供建议，以简化或协助标注过程。建议始终与现有问题相关联，始终是可选的，并且不仅包含建议本身，还包含其元数据（如果适用）。

  • (可选) label-suggestion 是 label_selection 类型，允许的值为 [0, 1, 2, 3]。

此外，还有两个可选字段：

• ✨ NEW metadata： 这是一个可选字段，用于提供有关数据集记录的额外信息。这可以为标注者提供额外的上下文，或提供有关数据集记录本身的额外信息。元数据始终是可选的，并且可以与 argilla.yaml 中的 metadata_properties 定义相关联。
• external_id： 这是一个可选字段，用于为数据集记录提供外部 ID。如果您想将数据集记录链接到外部资源（如数据库或文件），这可能很有用。

数据分割

数据集包含一个分割，即 train。