# ModernBERT-Biz-Trinary-Classifier-Fine_tuning - Fine-Tuning Dataset for Business Text Classification

## 📌 Overview
This dataset was used to fine-tune **ModernBERT-Biz-Trinary-Classifier**, a model that classifies text as:
- **Business_Action_Direct**: Clearly business-related (financial reports, funding rounds, revenue impact).
- **Business_Intelligence_Indirect**: Business-adjacent (economic trends, regulatory changes, potential business insights).
- **Not_Business_Relevant**: No meaningful business context.

The dataset includes a diverse mix of **social media posts, news articles, financial reports, forum discussions, and general text**, ensuring **robust business classification performance**.

## 📊 Dataset Statistics

| Total Samples | `83070` |

## 🛠 Features
- **text** (string): The raw input text.
- **Business_Action_Direct** (0/1): Whether the text contains direct business action.
- **Business_Intelligence_Indirect** (0/1): Whether the text contains indirect business intelligence.
- **Not_Business_Relevant** (0/1): Whether the text is not related to business.

## 🏗 Dataset Card
- **Author**: [Your Name / Organization]
- **License**: Apache 2.0
- **Tags**: `business-classification`, `text-classification`, `dataset`, `financial-analysis`