Update README.md

README.md

@@ -23,4 +23,56 @@ widget:
   example_title: "Spam"
 metrics:
 - f1
----
+---
+
+# 🛡️ Hybrid Chat + Email Spam Classifier (Encoder-Only, Multi-Turn)
+
+This repository provides a **lightweight, encoder-only multi-turn classifier** designed to detect spam and unwanted content across **emails** and **chat conversations**.
+
+It supports short and long messages, as well as **multi-turn conversational inputs** (meta data + message)
+
+It was trained using a mixed dataset emails, support chats, and messaging threads, using a 14B Teacher Model.
+
+This model is a fast-encoder only model, trained from distillation with a 14B Teacher Model on a 20M records dataset.
+
+---
+
+## ✨ Features
+
+- **Encoder-only architecture** → gives scores
+- **Multi-turn support** → handles conversation history and context windows
+- **Hybrid input domain** → optimized for both chat messages & email bodies
+- **High-throughput** → suitable for millions of messages/day
+- **Ideal for security filters** (spam, scams, phishing, self-promotion content)
+- **Open-source** and deployable anywhere (CPU or GPU)
+
+---
+
+## 🔧 Model Architecture
+
+- **Type:** Encoder-only (XLM Roberta Large)
+
+- **Input format:**
+
+[CONTEXT 1]
+[CONTEXT 2]
+...
+[USER MESSAGE]
+
+Labels include:
+
+- `spam`
+- `regular` (ham)
+- `marketing`
+- `gibberish`
+
+---
+
+## Benchmark
+
+- F1 Spam: 0.90
+- F1 Regular: 0.95
+- F1 Marketing: 0.87
+- F1 Gibberish: 0.94
+
+While this model is not perfect, it is excellent at quickly catching spam and is way better than bayesian filters.