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README.md

@@ -9,23 +9,17 @@ tags:
 - fraud-detection
 - distilbert
 - onnx
-datasets:
-- CEAS_08
-- Phishing_Email
-- enron_data_fraud_labeled
-- Nigerian_5
-- TREC_07
 pipeline_tag: text-classification
 ---
 
 # FraudFoxAI Phishing Detection Model
 
-Fine-tuned DistilBERT model for detecting phishing and fraudulent emails. Trained on 565,000+ emails from 5 datasets with 99.71% accuracy.
+Fine-tuned DistilBERT model for detecting phishing and fraudulent emails. Trained on 565,000+ curated emails with 99.71% accuracy.
 
 ## Model Details
 
 - **Base Model**: distilbert-base-uncased
-- **Training Data**: 565,293 emails from 5 combined datasets
+- **Training Data**: 565,293 curated emails from multiple sources
 - **Inference Runtime**: ONNX Runtime (PyTorch + ONNX available)
 - **Classes**: 
   - LABEL_0: Legitimate Email
@@ -42,14 +36,14 @@ Fine-tuned DistilBERT model for detecting phishing and fraudulent emails. Traine
 
 ## Training Data
 
-| Dataset | Emails | Description |
-|---|---|---|
-| Enron Fraud | 447,417 | Corporate fraud/legitimate emails |
-| TREC_07 | 53,757 | TREC spam detection corpus |
-| CEAS_08 | 39,154 | Conference on Email and Anti-Spam |
-| Phishing_Email | 18,634 | Labeled phishing/safe emails |
-| Nigerian_5 | 6,331 | 419/advance-fee fraud emails |
-| **Total** | **565,293** | |
+Trained on **565,293 curated emails** from multiple sources:
+
+- Corporate email archives (legitimate emails)
+- Reported phishing samples
+- Known 419/advance-fee fraud emails
+- Community-sourced spam and scam samples
+
+Continuously improved with user feedback.
 
 ## Training Configuration