Update README.md

README.md

@@ -30,4 +30,156 @@ configs:
     path: data/validation-*
   - split: test
     path: data/test-*
+license: apache-2.0
+task_categories:
+- numeric named entity recognition
+language:
+- gr
+tags:
+- finance
+- numeric
+pretty_name: Plutus Finner Numeric
+size_categories:
+- n<1K
 ---
+
+----------------------------------------------------------------
+# Dataset Card for Plutus Finner Numeric
+
+## 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/plutus-finner-numeric
+- **Repository:** https://huggingface.co/datasets/TheFinAI/plutus-finner-numeric
+- **Paper:** "Plutus: Benchmarking Large Language Models in Low-Resource Greek Finance"
+- **Leaderboard:** https://huggingface.co/spaces/TheFinAI/Open-Greek-Financial-LLM-Leaderboard#/
+- **Model:** https://huggingface.co/spaces/TheFinAI/plutus-8B-instruct
+
+### Dataset Summary
+
+Plutus Finner Numeric is a specialized dataset created for numeric named entity recognition within financial texts. It combines financial queries with associated answers, labels, and additional textual context, serving as a benchmark for identifying numeric entities in Greek language financial documents.
+
+### Supported Tasks and Leaderboards
+
+- **Task:** Numeric Named Entity Recognition
+- **Evaluation Metrics:** Entity F1 Score
+- **Test Size:** 100
+
+### Languages
+
+- Greek
+
+## Dataset Structure
+
+### Data Instances
+
+Each data instance in the dataset includes the following fields:
+
+- **query:** A financial query or prompt containing numeric expressions.
+- **answer:** The expected answer corresponding to the query.
+- **label:** A sequence field containing labels that may represent numeric entities or related categories.
+- **text:** Supplementary context or explanation accompanying each query.
+
+### Data Fields
+
+- **query:** String – The input prompt centered on financial numeric content.
+- **answer:** String – The answer intended for the corresponding query.
+- **label:** Sequence of strings – Additional labels or categorical descriptors for each instance.
+- **text:** String – Extra textual context or commentary.
+
+### Data Splits
+
+The dataset is divided into three splits:
+
+- **Train:** 320 instances (609,219 bytes)
+- **Validation:** 80 instances (166,639 bytes)
+- **Test:** 100 instances (219,566 bytes)
+
+## Dataset Creation
+
+### Curation Rationale
+
+The dataset was developed to support the evaluation of models in accurately identifying and reasoning with numeric entities in financial texts, specifically tailored for the Greek language. This is an essential resource for advancing research in numeric named entity recognition combined with financial text analysis in low-resource settings.
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+The source data was derived from a diverse collection of Greek financial annual reports containing numeric information. 
+
+#### Who are the Source Language Producers?
+
+Greek financial annual reports.
+
+### Annotations
+
+#### Annotation Process
+
+Annotations were performed by domain experts with backgrounds in finance and linguistics. The process involved identifying and labeling numeric entities based on financial context to facilitate accurate named entity recognition.
+
+#### Who are the Annotators?
+
+The dataset was annotated by a team of financial analysts, data scientists, and linguists collaborating to ensure both numeric accuracy and linguistic coherence.
+
+### Personal and Sensitive Information
+
+This dataset has been curated to exclude any personally identifiable information (PII). It focuses solely on financial content and numeric reasoning without sensitive personal data.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+By enhancing the capabilities of numeric named entity recognition in the financial domain, particularly in Greek, this dataset supports improved financial analysis, informed decision-making, and automated information processing. It is a valuable resource for both academic research and practical financial applications.
+
+### Discussion of Biases
+
+Potential biases include:
+- Domain-specific language and numeric formats that might be less applicable outside Greek financial texts.
+- The curation process may favor specific numeric presentation styles or financial topics.
+- Annotation variability inherent in domain-specific text processing.
+
+### Other Known Limitations
+
+- The dataset is specifically designed for Greek financial texts, which may limit its applicability to other domains or languages.
+- Variations in numeric expressions and formatting may require additional pre-processing before analysis.
+
+## Additional Information
+
+### Dataset Curators
+
+- The Fin AI Team
+
+### Licensing Information
+
+- **License:** Apache License 2.0
+
+### Citation Information
+
+If you use this dataset in your research, please consider citing it as follows:
+
+[Include appropriate citation details and DOIs when available.]