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---
size_categories: 1K<n<10K
tags:
- rlfh
- argilla
- human-feedback
---
# Dataset Card for my_setfit_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 --upgrade` and then use the following code:
```python
import argilla as rg
ds = rg.Dataset.from_hub("SeungAhSon/my_setfit_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("SeungAhSon/my_setfit_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 |
| ------------- | ----- | ---- | -------- | ----------- | ------------- |
| topics | Select the topic(s) of the request | multi_label_selection | True | N/A | ['activate_my_card', 'age_limit', 'apple_pay_or_google_pay', 'atm_support', 'automatic_top_up', 'balance_not_updated_after_bank_transfer', 'balance_not_updated_after_cheque_or_cash_deposit', 'beneficiary_not_allowed', 'cancel_transfer', 'card_about_to_expire', 'card_acceptance', 'card_arrival', 'card_delivery_estimate', 'card_linking', 'card_not_working', 'card_payment_fee_charged', 'card_payment_not_recognised', 'card_payment_wrong_exchange_rate', 'card_swallowed', 'cash_withdrawal_charge', 'cash_withdrawal_not_recognised', 'change_pin', 'compromised_card', 'contactless_not_working', 'country_support', 'declined_card_payment', 'declined_cash_withdrawal', 'declined_transfer', 'direct_debit_payment_not_recognised', 'disposable_card_limits', 'edit_personal_details', 'exchange_charge', 'exchange_rate', 'exchange_via_app', 'extra_charge_on_statement', 'failed_transfer', 'fiat_currency_support', 'get_disposable_virtual_card', 'get_physical_card', 'getting_spare_card', 'getting_virtual_card', 'lost_or_stolen_card', 'lost_or_stolen_phone', 'order_physical_card', 'passcode_forgotten', 'pending_card_payment', 'pending_cash_withdrawal', 'pending_top_up', 'pending_transfer', 'pin_blocked', 'receiving_money', 'Refund_not_showing_up', 'request_refund', 'reverted_card_payment?', 'supported_cards_and_currencies', 'terminate_account', 'top_up_by_bank_transfer_charge', 'top_up_by_card_charge', 'top_up_by_cash_or_cheque', 'top_up_failed', 'top_up_limits', 'top_up_reverted', 'topping_up_by_card', 'transaction_charged_twice', 'transfer_fee_charged', 'transfer_into_account', 'transfer_not_received_by_recipient', 'transfer_timing', 'unable_to_verify_identity', 'verify_my_identity', 'verify_source_of_funds', 'verify_top_up', 'virtual_card_not_working', 'visa_or_mastercard', 'why_verify_identity', 'wrong_amount_of_cash_received', 'wrong_exchange_rate_for_cash_withdrawal'] |
| sentiment | What is the sentiment of the message? | label_selection | True | N/A | ['positive', 'neutral', 'negative'] |
<!-- check length of metadata properties -->
### Data Instances
An example of a dataset instance in Argilla looks as follows:
```json
{
"_server_id": "70e66e5f-32a6-4376-9b89-48c355365e56",
"fields": {
"text": "I need to reset my passcode. How do I do it?"
},
"id": "74194048-4270-4e14-b5d8-58193abd969c",
"metadata": {},
"responses": {},
"status": "pending",
"suggestions": {
"sentiment": {
"agent": null,
"score": null,
"value": "neutral"
},
"topics": {
"agent": null,
"score": null,
"value": [
"passcode_forgotten"
]
}
},
"vectors": {}
}
```
While the same record in HuggingFace `datasets` looks as follows:
```json
{
"_server_id": "70e66e5f-32a6-4376-9b89-48c355365e56",
"id": "74194048-4270-4e14-b5d8-58193abd969c",
"sentiment.suggestion": "neutral",
"sentiment.suggestion.agent": null,
"sentiment.suggestion.score": null,
"status": "pending",
"text": "I need to reset my passcode. How do I do it?",
"topics.suggestion": [
"passcode_forgotten"
],
"topics.suggestion.agent": null,
"topics.suggestion.score": 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] |