Duplicate from cybersectony/PhishingEmailDetectionv2.0

Co-authored-by: Tony Kiplagat Cheptoo <cybersectony@users.noreply.huggingface.co>

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README.md

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+---
+dataset_info:
+  features:
+  - name: content
+    dtype: string
+  - name: label
+    dtype: int64
+  splits:
+  - name: train
+    num_bytes: 47241927
+    num_examples: 120000
+  - name: validation
+    num_bytes: 5052323
+    num_examples: 20000
+  - name: test
+    num_bytes: 14856442
+    num_examples: 60000
+  download_size: 40289388
+  dataset_size: 67150692
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: validation
+    path: data/validation-*
+  - split: test
+    path: data/test-*
+---
+
+# Phishing Email Detection Dataset
+
+A comprehensive dataset combining email messages and URLs for phishing detection.
+
+## Dataset Overview
+
+### Quick Facts
+- **Task Type**: Multi-class Classification
+- **Languages**: English
+- **Total Samples**: 200,000 entries
+- **Size Split**: 
+  - Email samples: 22,644
+  - URL samples: 177,356
+- **Label Distribution**: Four classes (0, 1, 2, 3)
+- **Format**: Two columns - `content` and `labels`
+
+## Dataset Structure
+
+### Features
+```python
+{
+    'content': Value(dtype='string', description='The text content - either email body or URL'),
+    'labels': ClassLabel(num_classes=4, names=[
+        'legitimate_email',    # 0
+        'phishing_email',       # 1
+        'legitimate_url',     # 2
+        'phishing_url'    # 3
+    ], description='Multi-class label for content classification')
+}

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