argilla/end2end_textclassification

1---2size_categories: 1K<n<10K3tags:4- rlfh5- argilla6- human-feedback7---8 9# Dataset Card for end2end_textclassification10 11This dataset has been created with [Argilla](https://docs.argilla.io).12 13As 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).14 15## Dataset Description16 17- **Homepage:** https://argilla.io18- **Repository:** https://github.com/argilla-io/argilla19- **Paper:** 20- **Leaderboard:** 21- **Point of Contact:** 22 23### Dataset Summary24 25This dataset contains:26 27* 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.28 29* 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`.30 31* The [annotation guidelines](#annotation-guidelines) that have been used for building and curating the dataset, if they've been defined in Argilla.32 33### Load with Argilla34 35To load with Argilla, you'll just need to install Argilla as `pip install argilla --upgrade` and then use the following code:36 37```python38import argilla as rg39 40ds = rg.FeedbackDataset.from_huggingface("argilla/end2end_textclassification")41```42 43### Load with `datasets`44 45To load this dataset with `datasets`, you'll just need to install `datasets` as `pip install datasets --upgrade` and then use the following code:46 47```python48from datasets import load_dataset49 50ds = load_dataset("argilla/end2end_textclassification")51```52 53### Supported Tasks and Leaderboards54 55This 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).56 57There are no leaderboards associated with this dataset.58 59### Languages60 61[More Information Needed]62 63## Dataset Structure64 65### Data in Argilla66 67The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, **metadata**, **vectors**, and **guidelines**.68 69The **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.70 71| Field Name | Title | Type | Required | Markdown |72| ---------- | ----- | ---- | -------- | -------- |73| text | Text | text | True | False |74 75 76The **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.77 78| Question Name | Title | Type | Required | Description | Values/Labels |79| ------------- | ----- | ---- | -------- | ----------- | ------------- |80| label | Label | label_selection | True | Classify the text by selecting the correct label from the given list of labels. | ['World', 'Sports', 'Business', 'Sci/Tech'] |81 82 83The **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".84 85The **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`.86 87 88 89| Metadata Name | Title | Type | Values | Visible for Annotators |90| ------------- | ----- | ---- | ------ | ---------------------- |91 92 93The **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.94 95### Data Instances96 97An example of a dataset instance in Argilla looks as follows:98 99```json100{101    "external_id": "record-0",102    "fields": {103        "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."104    },105    "metadata": {},106    "responses": [],107    "suggestions": [],108    "vectors": {}109}110```111 112While the same record in HuggingFace `datasets` looks as follows:113 114```json115{116    "external_id": "record-0",117    "label": [],118    "label-suggestion": null,119    "label-suggestion-metadata": {120        "agent": null,121        "score": null,122        "type": null123    },124    "metadata": "{}",125    "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."126}127```128 129### Data Fields130 131Among the dataset fields, we differentiate between the following:132 133* **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.134    135    * **text** is of type `text`.136 137* **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`.138    139    * **label** is of type `label_selection` with the following allowed values ['World', 'Sports', 'Business', 'Sci/Tech'], and description "Classify the text by selecting the correct label from the given list of labels.".140 141* **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.142    143    * (optional) **label-suggestion** is of type `label_selection` with the following allowed values ['World', 'Sports', 'Business', 'Sci/Tech'].144 145 146 147Additionally, we also have two more fields that are optional and are the following:148 149* **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`.150* **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.151 152### Data Splits153 154The dataset contains a single split, which is `train`.155 156## Dataset Creation157 158### Curation Rationale159 160[More Information Needed]161 162### Source Data163 164#### Initial Data Collection and Normalization165 166[More Information Needed]167 168#### Who are the source language producers?169 170[More Information Needed]171 172### Annotations173 174#### Annotation guidelines175 176Classify the articles into one of the four categories.177 178#### Annotation process179 180[More Information Needed]181 182#### Who are the annotators?183 184[More Information Needed]185 186### Personal and Sensitive Information187 188[More Information Needed]189 190## Considerations for Using the Data191 192### Social Impact of Dataset193 194[More Information Needed]195 196### Discussion of Biases197 198[More Information Needed]199 200### Other Known Limitations201 202[More Information Needed]203 204## Additional Information205 206### Dataset Curators207 208[More Information Needed]209 210### Licensing Information211 212[More Information Needed]213 214### Citation Information215 216[More Information Needed]217 218### Contributions219 220[More Information Needed]