Update README.md

README.md

@@ -1,3 +1,31 @@
+---
+language:
+- en
+license: mit
+tags:
+- text-classification
+- naive-bayes
+- tf-idf
+- english-nlp
+- spam-detection
+pipeline_tag: text-classification
+metrics:
+- accuracy
+model-index:
+- name: Spam Detection — English (Naive Bayes)
+  results:
+  - task:
+      type: text-classification
+      name: Text Classification
+    dataset:
+      name: English Spam Dataset
+      type: custom
+    metrics:
+    - type: accuracy
+      value: 0.994
+      name: Accuracy
+---
+
 # Spam Detection — English (Naive Bayes)
 
 A lightweight spam/ham text classifier for English messages, built with a 
@@ -17,16 +45,9 @@ multilingual spam detection system that automatically routes text to a
 language-specific model (English or Arabic) based on detected language.
 
 ## How to Use
-\```python
+```python
 import joblib
 
 model = joblib.load("spam_eng_nb.joblib")
 prediction = model.predict(["Congratulations! You've won a free prize, click here now"])
-print(prediction)  # 1 = spam, 0 = ham
-\```
-
-## Limitations
-- Trained on a specific dataset distribution; may not generalize well to 
-  domains very different from training data (e.g. highly technical or 
-  slang-heavy text)
-- Naive Bayes assumes word independence — does not capture context or word order
+print(prediction)  # 1 = spam, 0 = ham