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---
license: mit
tags:
- nifty
- stock-movement
- news-and-events
- RLMF
task_categories:
- multiple-choice
- time-series-forecasting
- document-question-answering
task_ids:
- topic-classification
- semantic-similarity-classification
- multiple-choice-qa
- univariate-time-series-forecasting
- document-question-answering
language:
- en
pretty_name: nifty-rl
size_categories:
- 1K<n<100k
configs:
- config_name: nifty-rl
data_files:
- split: train
path: "train.jsonl"
- split: test
path: "test.jsonl"
- split: valid
path: "valid.jsonl"
default: true
---
<h1>
<img alt="RH" src="./nifty-icon.png" style="display:inline-block; vertical-align:middle; width:120px; height:120px; object-fit:contain" />
The News-Informed Financial Trend Yield (NIFTY) Dataset.
</h1>
The News-Informed Financial Trend Yield (NIFTY) Dataset. Details of the dataset, including data procurement and filtering can be found in the paper here: https://arxiv.org/abs/2405.09747.
## 📋 Table of Contents
- [🧩 NIFTY Dataset](#nifty-dataset)
- [📋 Table of Contents](#table-of-contents)
- [📖 Usage](#usage)
- [Downloading the dataset](#downloading-the-dataset)
- [Dataset structure](#dataset-structure)
- [Large Language Models](#large-language-models)
- [✍️ Contributing](#contributing)
- [📝 Citing](#citing)
- [🙏 Acknowledgements](#acknowledgements)
## 📖 [Usage](#usage)
Downloading and using this dataset should be straight-forward following the Huggingface datasets framework.
### [Downloading the dataset](#downloading-the-dataset)
The NIFTY dataset is available on huggingface [here](https://huggingface.co/datasets/raeidsaqur/NIFTY) and can be downloaded with the following python snipped:
```python
from datasets import load_dataset
# If the dataset is gated/private, make sure you have run huggingface-cli login
dataset = load_dataset("raeidsaqur/nifty-rl")
```
### [Dataset structure](#dataset-structure)
The dataset is split into 3 partition, train, valid and test and each partition is a jsonl file where a single row has the following keys.
```python
['prompt', 'chosen', 'rejected', 'chosen_label', 'chosen_value']
```
Currently, the dataset has 2111 examples in total, the dates randing from 2010-01-06 to 2020-09-21.
<!-- The number of examples for each split is given below.
| Split | Num Examples | Date range |
|-------|--------------|------------|
|Train |1477 |2010-01-06 - 2017-06-27 |
|Valid|317 | 2017-06-28- 2019-02-12|
|Test |317|2019-02-13 - 2020-09-21|
-->
<!--
<img alt="St" src="./imgs/visualize_nifty_1794_2019-02-13.png"
style="display:inline-block; vertical-align:middle; width:640px;
height:640px; object-fit:contain" />
-->
## ✍️ [Contributing](#contributing)
We welcome contributions to this repository (noticed a typo? a bug?). To propose a change:
```
git clone https://huggingface.co/datasets/raeidsaqur/nifty-rl
cd nifty-rl
git checkout -b my-branch
pip install -r requirements.txt
pip install -e .
```
Once your changes are made, make sure to lint and format the code (addressing any warnings or errors):
```
isort .
black .
flake8 .
```
Then, submit your change as a pull request.
## 📝 [Citing](#citing)
If you use the NIFTY Financial dataset in your work, please consider citing our paper:
```
@article{raeidsaqur2024NiftyRL,
title = {NIFTY-RL: Financial News Headlines Dataset for LLM Alignment using Reinforcement Learning.},
author = {Raeid Saqur},
year = 2024,
journal = {ArXiv},
url = {https://arxiv.org/abs/2024.5599314}
}
```
## 🙏 [Acknowledgements](#acknowledgements)
The authors acknowledge and thank the generous computing provided by the Vector Institute, Toronto.
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