Update README.md

README.md

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----
-dataset_info:
-  features:
-  - name: text
-    dtype: string
-  - name: email_type
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 20821235
-    num_examples: 26946
-  - name: test
-    num_bytes: 3307336
-    num_examples: 3705
-  download_size: 12901354
-  dataset_size: 24128571
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
----
+```markdown
+# 🛡️ Phishing Email Classification Dataset
+
+This dataset is curated for fine-tuning LLMs on the task of phishing email detection. It originates from [this Kaggle dataset](https://www.kaggle.com/datasets/subhajournal/phishingemails) and has been transformed to better suit LLM-based classification tasks.
+
+## 📦 Dataset Features
+
+- Each row is a labeled email, with either:
+  - `safe email` (label = 0)
+  - `phishing email` (label = 1)
+- The dataset includes metadata (sender, receiver, date, subject) and cleaned email body.
+- Two main columns:
+  - `Email Text`: Complete formatted text including metadata and message content.
+  - `label`: Binary label indicating if the email is phishing.
+
+## 🧠 LLM Fine-Tuning Ready
+
+Processed using a `phishing_items.py` parser:
+- Truncates or filters emails based on token limits for LLM input (between 30 and 250 tokens).
+- Builds classification prompts in the format:
+  
+  ```
+  Is the following email safe or phishing??
+
+  [email content]
+
+  Email type is: [safe email/phishing email]
+  ```
+
+- Optimized for models such as `meta-llama/Meta-Llama-3.1-8B`.
+
+## 🧼 Preprocessing Highlights
+
+- Removes non-informative characters (e.g., `=`, `>`, `\`) and extra whitespace.
+- Tokenized with Hugging Face's `AutoTokenizer`.
+- Discards overly short emails (under 120 characters or under 30 tokens).
+
+## 🗂️ Example Usage
+
+```python
+from phishing_items import Item
+
+item = Item(data_row)
+if item.include:
+    print(item.prompt)
+```
+
+## 📚 Source
+
+- Original dataset: [Kaggle - Phishing Emails](https://www.kaggle.com/datasets/subhajournal/phishingemails)
+- Transformed by: [your GitHub or Hugging Face handle]
+```