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 Jayesh2732







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("wyzard-ai/Jayesh2732", 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("wyzard-ai/Jayesh2732")
```

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 |
| ---------- | ----- | ---- | -------- | -------- |
| instruction | User instruction | text | True | True |


### 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 |
| ------------- | ----- | ---- | -------- | ----------- | ------------- |
| relevance_score | How Relevant is the conversation based upon expert. Is the conversation highly curated for you or not. Please don't judge accuracy. | rating | True | N/A | [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] |
| accuracy_score | How accurate is the conversation based upon persona | rating | True | if  | [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] |
| clarity_score | How clear is the conversation based upon persona | rating | True | Is the LLM getting confused | [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] |
| actionable_score | How actionable is the conversation based upon persona | rating | True | Is the LLM response to actionable for example, it shows comparison card on the right question.  | [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] |
| engagement_score | How engaging is the conversation based upon persona | rating | True | Are there a lot of question that are being shown if yes, high score else low score | [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] |
| completeness_score | is the conversation complete based upon persona | rating | True | is the conversation complete based upon persona, not leaving any key aspect out | [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] |
| feedback | feedback | text | True | What do you think can be improved in the given conversation. How good was the conversation as per you? | 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 |
| ------------- | ----- | ---- | ------ | ---------------------- |
 | conv_id | Conversation ID |  |  -  | True |
 | turn | Conversation Turn |  | 0 - 100 | True |






### Data Instances

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

```json
{
    "_server_id": "63d40792-3def-4435-a591-af4506143733",
    "fields": {
        "instruction": "**user**: hi\n**assistant**: Hello Jayesh! How can I assist you today? Are you looking for insights on development software or perhaps some advice on the latest programming tools?"
    },
    "id": "e47d050a-0605-4511-8c25-b802c6fce8e8",
    "metadata": {
        "conv_id": "9999eb70-c3c7-4ff5-b533-db0b7b7ba963",
        "turn": 0
    },
    "responses": {},
    "status": "pending",
    "suggestions": {},
    "vectors": {}
}
```

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

```json
{
    "_server_id": "63d40792-3def-4435-a591-af4506143733",
    "conv_id": "9999eb70-c3c7-4ff5-b533-db0b7b7ba963",
    "id": "e47d050a-0605-4511-8c25-b802c6fce8e8",
    "instruction": "**user**: hi\n**assistant**: Hello Jayesh! How can I assist you today? Are you looking for insights on development software or perhaps some advice on the latest programming tools?",
    "status": "pending",
    "turn": 0
}
```


### 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

Review the user interactions with the chatbot.

#### 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]