Update README.md

README.md

@@ -19,7 +19,174 @@ dataset_info:
     num_examples: 496
   download_size: 140144
   dataset_size: 384180
+license: cc-by-nc-4.0
+task_categories:
+- text-classification
+language:
+- en
+tags:
+- finance
+pretty_name: FinBen FOMC
+size_categories:
+- n<1K
 ---
-# Dataset Card for "flare-fomc"
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+---
+
+# Dataset Card for FinBen-FOMC
+
+## Table of Contents
+
+- [Table of Contents](#table-of-contents)
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** https://huggingface.co/datasets/TheFinAI/finben-fomc
+- **Repository:** https://huggingface.co/datasets/TheFinAI/finben-fomc
+- **Paper:** FinBen: An Holistic Financial Benchmark for Large Language Models
+- **Leaderboard:** https://huggingface.co/spaces/finosfoundation/Open-Financial-LLM-Leaderboard
+
+### Dataset Summary
+
+FinBen-FOMC is a financial sentiment classification dataset adapted from **FOMC (Shah et al., 2023a)**. The dataset is designed for training and evaluating large language models (LLMs) on classifying central bank policy stances as **Hawkish, Dovish, or Neutral**.
+
+### Supported Tasks and Leaderboards
+
+- **Task:** Hawkish-Dovish Classification
+- **Evaluation Metric:** F1 Score, Accuracy
+- **Test Size:** 496 instances
+
+### Languages
+
+- English
+
+## Dataset Structure
+
+### Data Instances
+
+Each instance consists of a structured format with the following fields:
+
+- **id**: A unique identifier for each data instance.
+- **query**: An excerpt from a central bank’s release.
+- **answer**: The classification label (`HAWKISH`, `DOVISH`, or `NEUTRAL`).
+
+### Data Fields
+
+- **id**: Unique string identifier for the data instance.
+- **query**: The input text containing an excerpt from a central bank statement.
+- **answer**: The classification label (`HAWKISH`, `DOVISH`, or `NEUTRAL`).
+
+### Data Splits
+
+The dataset is split into:
+
+- **Test:** 496 instances
+
+## Dataset Creation
+
+### Curation Rationale
+
+The dataset is adapted from **FOMC (Shah et al., 2023a)** to improve its suitability for LLM-based classification tasks in central bank policy analysis.
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+The dataset originates from Federal Open Market Committee (FOMC) statements and other central bank releases.
+
+#### Who are the source language producers?
+
+Central bank officials and policy documents.
+
+### Annotations
+
+#### Annotation Process
+
+Annotations follow a structured classification framework to label monetary policy stances.
+
+#### Who are the annotators?
+
+Financial experts and researchers.
+
+### Personal and Sensitive Information
+
+No personally identifiable information (PII) is included.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+This dataset enhances financial NLP capabilities, allowing more accurate analysis of monetary policy signals.
+
+### Discussion of Biases
+
+Potential biases may exist due to:
+
+- Interpretation differences in policy statements.
+- Variability in central bank language across periods.
+
+### Other Known Limitations
+
+- Requires financial domain expertise for best model performance.
+- May not generalize well to non-FOMC policy documents.
+
+## Additional Information
+
+### Dataset Curators
+
+- The Fin AI Team
+
+### Licensing Information
+
+- **License:** CC BY-NC 4.0
+
+### Citation Information
+
+**Original Dataset:**
+
+```bibtex
+@inproceedings{shah2023trillion,
+  title={Trillion Dollar Words: A New Financial Dataset, Task & Market Analysis},
+  author={Shah, Agam and Paturi, Suvan and Chava, Sudheer},
+  booktitle={Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
+  editor={Anna Rogers, Jordan Boyd-Graber, and Naoaki Okazaki},
+  pages={6664--6679},
+  year={2023},
+  organization={Association for Computational Linguistics},
+  address={Toronto, Canada},
+  doi={10.18653/v1/2023.acl-long.368}
+}
+```
+
+**Adapted Version (FinBen-FOMC):**
+
+```bibtex
+@article{xie2024finben,
+  title={FinBen: A Holistic Financial Benchmark for Large Language Models},
+  author={Xie, Qianqian and others},
+  journal={arXiv preprint arXiv:2402.12659},
+  year={2024}
+}
+```