size_categories:n<1K format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars library:argilla region:us rlfh argilla human-feedback
---
size_categories: n<1K
tags:
- rlfh
- argilla
- human-feedback
---

# Dataset Card for domain_classication_1







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 --upgrade` and then use the following code:

```python
import argilla as rg

ds = rg.Dataset.from_hub("chrononeel/domain_classication_1", settings="auto")
```

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("chrononeel/domain_classication_1")
```

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 |
| ---------- | ----- | ---- | -------- | -------- |
| input | Bangla Input | text | True | False |
| instruction | Bangla Instruction | text | True | False |
| output | Bangla Output | 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 |
| ------------- | ----- | ---- | -------- | ----------- | ------------- |
| domain_classification | Select the most suitable domain for this input, instruction and output | label_selection | True | N/A | ['Life science and Wellness', 'Physics and Chemistry', 'Math', 'Programming and Web Development', 'Artificial Intelligence', 'Environmental Science and Sustainability', 'Ethics, Philosophy and Religion', 'History and Social Science', 'Grammar and Language Processing', 'Creative Writing and Literature', 'Personal and Career Decision Making', 'Tech', 'Business & Economics', 'Law & Public Policy', 'Media & Entertainment', 'Sports and Recreation', 'Miscellaneous'] |


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### Data Instances

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

```json
{
    "_server_id": "20d23e89-1b9f-4f8f-b1de-6e7de407916b",
    "fields": {
        "input": "",
        "instruction": "\u09a4\u09bf\u09a8\u099f\u09bf \u09aa\u09cd\u09b0\u09a7\u09be\u09a8 \u09b0\u0999 \u0995\u09bf \u0995\u09bf?",
        "output": "\u09a4\u09bf\u09a8\u099f\u09bf \u09aa\u09cd\u09b0\u09be\u09a5\u09ae\u09bf\u0995 \u09b0\u0999 \u09b9\u09b2 \u09b2\u09be\u09b2, \u09a8\u09c0\u09b2 \u098f\u09ac\u0982 \u09b9\u09b2\u09c1\u09a6\u0964 \u098f\u0987 \u09b0\u0999\u0997\u09c1\u09b2\u09bf\u0995\u09c7 \u09aa\u09cd\u09b0\u09be\u09a5\u09ae\u09bf\u0995 \u09ac\u09b2\u09be \u09b9\u09af\u09bc \u0995\u09be\u09b0\u09a3 \u098f\u0997\u09c1\u09b2\u09bf \u0985\u09a8\u09cd\u09af\u09be\u09a8\u09cd\u09af \u09b0\u0999\u09c7\u09b0 \u09ae\u09bf\u09b6\u09cd\u09b0\u09a3 \u09a6\u09cd\u09ac\u09be\u09b0\u09be \u09a4\u09c8\u09b0\u09bf \u0995\u09b0\u09be \u09af\u09be\u09af\u09bc \u09a8\u09be \u098f\u09ac\u0982 \u0985\u09a8\u09cd\u09af\u09be\u09a8\u09cd\u09af \u09b8\u09ae\u09b8\u09cd\u09a4 \u09b0\u0999 \u09ac\u09bf\u09ad\u09bf\u09a8\u09cd\u09a8 \u0985\u09a8\u09c1\u09aa\u09be\u09a4\u09c7 \u09a4\u09be\u09a6\u09c7\u09b0 \u098f\u0995\u09a4\u09cd\u09b0\u09bf\u09a4 \u0995\u09b0\u09c7 \u09a4\u09c8\u09b0\u09bf \u0995\u09b0\u09be \u09af\u09c7\u09a4\u09c7 \u09aa\u09be\u09b0\u09c7\u0964 \u09b8\u0982\u09af\u09cb\u099c\u09a8 \u09b0\u0999\u09c7\u09b0 \u09ac\u09cd\u09af\u09ac\u09b8\u09cd\u09a5\u09be\u09af\u09bc, \u0986\u09b2\u09cb \u099c\u09a8\u09cd\u09af \u09ac\u09cd\u09af\u09ac\u09b9\u09c3\u09a4, \u09aa\u09cd\u09b0\u09be\u09a5\u09ae\u09bf\u0995 \u09b0\u0999\u0997\u09c1\u09b2\u09bf \u09b9\u09b2 \u09b2\u09be\u09b2, \u09b8\u09ac\u09c1\u099c \u098f\u09ac\u0982 \u09a8\u09c0\u09b2 (\u0986\u09b0\u099c\u09bf\u09ac\u09bf) \u0964"
    },
    "id": "4e5b5ae5-6af6-41d0-ac2e-065b74682b86",
    "metadata": {},
    "responses": {},
    "status": "pending",
    "suggestions": {},
    "vectors": {}
}
```

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

```json
{
    "_server_id": "20d23e89-1b9f-4f8f-b1de-6e7de407916b",
    "domain_classification.responses": null,
    "domain_classification.responses.status": null,
    "domain_classification.responses.users": null,
    "id": "4e5b5ae5-6af6-41d0-ac2e-065b74682b86",
    "input": "",
    "instruction": "\u09a4\u09bf\u09a8\u099f\u09bf \u09aa\u09cd\u09b0\u09a7\u09be\u09a8 \u09b0\u0999 \u0995\u09bf \u0995\u09bf?",
    "output": "\u09a4\u09bf\u09a8\u099f\u09bf \u09aa\u09cd\u09b0\u09be\u09a5\u09ae\u09bf\u0995 \u09b0\u0999 \u09b9\u09b2 \u09b2\u09be\u09b2, \u09a8\u09c0\u09b2 \u098f\u09ac\u0982 \u09b9\u09b2\u09c1\u09a6\u0964 \u098f\u0987 \u09b0\u0999\u0997\u09c1\u09b2\u09bf\u0995\u09c7 \u09aa\u09cd\u09b0\u09be\u09a5\u09ae\u09bf\u0995 \u09ac\u09b2\u09be \u09b9\u09af\u09bc \u0995\u09be\u09b0\u09a3 \u098f\u0997\u09c1\u09b2\u09bf \u0985\u09a8\u09cd\u09af\u09be\u09a8\u09cd\u09af \u09b0\u0999\u09c7\u09b0 \u09ae\u09bf\u09b6\u09cd\u09b0\u09a3 \u09a6\u09cd\u09ac\u09be\u09b0\u09be \u09a4\u09c8\u09b0\u09bf \u0995\u09b0\u09be \u09af\u09be\u09af\u09bc \u09a8\u09be \u098f\u09ac\u0982 \u0985\u09a8\u09cd\u09af\u09be\u09a8\u09cd\u09af \u09b8\u09ae\u09b8\u09cd\u09a4 \u09b0\u0999 \u09ac\u09bf\u09ad\u09bf\u09a8\u09cd\u09a8 \u0985\u09a8\u09c1\u09aa\u09be\u09a4\u09c7 \u09a4\u09be\u09a6\u09c7\u09b0 \u098f\u0995\u09a4\u09cd\u09b0\u09bf\u09a4 \u0995\u09b0\u09c7 \u09a4\u09c8\u09b0\u09bf \u0995\u09b0\u09be \u09af\u09c7\u09a4\u09c7 \u09aa\u09be\u09b0\u09c7\u0964 \u09b8\u0982\u09af\u09cb\u099c\u09a8 \u09b0\u0999\u09c7\u09b0 \u09ac\u09cd\u09af\u09ac\u09b8\u09cd\u09a5\u09be\u09af\u09bc, \u0986\u09b2\u09cb \u099c\u09a8\u09cd\u09af \u09ac\u09cd\u09af\u09ac\u09b9\u09c3\u09a4, \u09aa\u09cd\u09b0\u09be\u09a5\u09ae\u09bf\u0995 \u09b0\u0999\u0997\u09c1\u09b2\u09bf \u09b9\u09b2 \u09b2\u09be\u09b2, \u09b8\u09ac\u09c1\u099c \u098f\u09ac\u0982 \u09a8\u09c0\u09b2 (\u0986\u09b0\u099c\u09bf\u09ac\u09bf) \u0964",
    "status": "pending"
}
```


### 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

Classify each data based on its domain

#### 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]