--- size_categories: n<1K tags: - rlfh - argilla - human-feedback --- # Dataset Card for test-argilla-dataset This dataset has been created with [Argilla](https://argilla-io.github.io). - **Homepage:** https://argilla.io - **Repository:** https://github.com/argilla-io/argilla - **Paper:** - **Leaderboard:** - **Point of Contact:** 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). This dataset 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`. ## Using this dataset ### Load 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 the Argilla instance. ### Load 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 ### Data in Argilla The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, **metadata**, **vectors**, and **guidelines**. The **fields** are the dataset samples like a 'text' field. | Field Name | Title | Type | Required | Markdown | | ---------- | ----- | ---- | -------- | -------- | | text | text | 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 | 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 | 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 | The **vectors** contain a vector representation of the record that can be used in search. | Vector Name | Title | Dimensions | |-------------|-------|------------| | vector | vector | [1, 3] | 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 "{\"id\":\"b583ab1c-6765-4915-94ff-245172fa92a9\",\"inserted_at\":null,\"updated_at\":null,\"fields\":{\"text\":\"Hello World, how are you?\"},\"metadata\":{},\"vectors\":{},\"responses\":[{\"values\":{\"label\":{\"value\":\"positive\"}},\"status\":\"draft\",\"user_id\":\"06f7d4c0-e048-43d2-ab3f-06f147616ac6\"}],\"suggestions\":[{\"value\":\"positive\",\"question_name\":\"label\",\"type\":null,\"score\":null,\"agent\":null,\"id\":\"49c86119-669f-4702-bc14-eb7f4da2bb9d\",\"question_id\":\"890c7c5b-d068-411d-9626-52b9ba49c8f5\"},{\"value\":[\"topic1\",\"topic2\"],\"question_name\":\"topics\",\"type\":null,\"score\":[0.9,0.8],\"agent\":null,\"id\":\"208722a7-4f5d-4bf8-a422-f92b8d8d589c\",\"question_id\":\"fc60838a-a0ad-4678-bad9-a86017585aff\"}],\"external_id\":\"8374351f-20ee-492e-afde-216958053b0f\"}" ``` While the same record in HuggingFace `datasets` looks as follows: ```json { "_server_id": "b583ab1c-6765-4915-94ff-245172fa92a9", "comment.suggestion": null, "comment.suggestion.agent": null, "comment.suggestion.score": null, "comment_score": null, "id": "8374351f-20ee-492e-afde-216958053b0f", "label.responses": [ "positive" ], "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]