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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