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README.md

@@ -1,23 +1,25 @@
----
-dataset_info:
-  features:
-  - name: text
-    dtype: string
-  - name: Business_Intelligence_Indirect
-    dtype: int64
-  - name: Business_Action_Direct
-    dtype: int64
-  - name: Not_Business_Relevant
-    dtype: int64
-  splits:
-  - name: train
-    num_bytes: 153367339
-    num_examples: 83070
-  download_size: 87218016
-  dataset_size: 153367339
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
----
+
+# 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`