README.md

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

# Dataset Card for test-argilla-dataset







This dataset has been created with [Argilla](https://github.com/argilla-io/argilla). As shown in the sections below, this dataset can be loaded into your Argilla server as explained in [Load with Argilla](#load-with-argilla), or used directly with the `datasets` library in [Load with `datasets`](#load-with-datasets).


## Using this dataset with Argilla

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

```python
import argilla as rg

ds = rg.Dataset.from_hub("burtenshaw/test-argilla-dataset")
```

This will load the settings and records from the dataset repository and push them to you Argilla server for exploration and annotation.

## Using this dataset with `datasets`

To load the records of 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("burtenshaw/test-argilla-dataset")
```

This will only load the records of the dataset, but not the Argilla settings.

## Dataset Structure

This dataset repo contains:

* Dataset records in a format compatible with HuggingFace `datasets`. These records will be loaded automatically when using `rg.Dataset.from_hub` 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.
* A dataset configuration folder conforming to the Argilla dataset format in `.argilla`.

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

### Fields

The **fields** are the features or text of a dataset's records. For example, the 'text' column of a text classification dataset of the 'prompt' column of an instruction following dataset.

| Field Name | Title | Type | Required | Markdown |
| ---------- | ----- | ---- | -------- | -------- |
| text | text | text | True | False |


### Questions

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 | label | label_selection | True | N/A | ['positive', 'negative'] |
| rating | rating | rating | True | N/A | [1, 2, 3, 4, 5] |
| ranking | ranking | ranking | True | N/A | ['label1', 'label2', 'label3'] |
| comment | comment | text | True | N/A | N/A |
| topics | topics | multi_label_selection | True | N/A | ['topic1', 'topic2', 'topic3'] |
| span | span | span | True | N/A | N/A |


<!-- check length of metadata properties -->

### Metadata

The **metadata** is a dictionary that can be used to provide additional information about the dataset record.
| Metadata Name | Title | Type | Values | Visible for Annotators |
| ------------- | ----- | ---- | ------ | ---------------------- |
 | comment_score | comment_score |  | None - None | True |




### Vectors
The **vectors** contain a vector representation of the record that can be used in  search.

| Vector Name | Title | Dimensions |
|-------------|-------|------------|
| vector | vector | [1, 3] |




### Data Instances

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

```json
{
    "_server_id": "8aaf57d2-cb8e-4673-a7ce-2f684b60adf5",
    "fields": {
        "text": "Hello World, how are you?"
    },
    "id": "4f56e32b-9582-47de-a2b1-b230732bb07b",
    "metadata": {},
    "responses": {
        "label": [
            {
                "user_id": "06f7d4c0-e048-43d2-ab3f-06f147616ac6",
                "value": "positive"
            }
        ]
    },
    "suggestions": {
        "label": {
            "agent": null,
            "score": null,
            "value": "positive"
        },
        "topics": {
            "agent": null,
            "score": [
                0.9,
                0.8
            ],
            "value": [
                "topic1",
                "topic2"
            ]
        }
    },
    "vectors": {}
}
```

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

```json
{
    "_server_id": "8aaf57d2-cb8e-4673-a7ce-2f684b60adf5",
    "comment.suggestion": null,
    "comment.suggestion.agent": null,
    "comment.suggestion.score": null,
    "comment_score": null,
    "id": "4f56e32b-9582-47de-a2b1-b230732bb07b",
    "label.responses": [
        "positive"
    ],
    "label.responses.status": [
        "draft"
    ],
    "label.responses.users": [
        "06f7d4c0-e048-43d2-ab3f-06f147616ac6"
    ],
    "label.suggestion": "positive",
    "label.suggestion.agent": null,
    "label.suggestion.score": null,
    "ranking.suggestion": null,
    "ranking.suggestion.agent": null,
    "ranking.suggestion.score": null,
    "rating.suggestion": null,
    "rating.suggestion.agent": null,
    "rating.suggestion.score": null,
    "span.suggestion": null,
    "span.suggestion.agent": null,
    "span.suggestion.score": null,
    "text": "Hello World, how are you?",
    "topics.suggestion": [
        "topic1",
        "topic2"
    ],
    "topics.suggestion.agent": null,
    "topics.suggestion.score": [
        0.9,
        0.8
    ],
    "vector": null
}
```


### 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

[More Information Needed]

#### 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]