Update README.md

README.md

@@ -7,30 +7,209 @@ tags:
 model-index:
 - name: help-classifier-v2
   results: []
+datasets:
+- King-8/help-request-messages-v2
 ---
+# 🤖 Help Classifier Model (v2)
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+## 🧠 Overview
 
-# help-classifier-v2
+The **Help Classifier Model (v2)** is a fine-tuned NLP model designed to classify student help requests into meaningful categories within a collaborative learning environment.
 
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.0643
+This model is part of a larger AI system built for the **Coding in Color (CIC)** ecosystem, supporting students working across domains such as AI development, game development, 2D/3D art, and robotics.
+
+Its primary purpose is to:
+
+* Interpret real student messages
+* Identify intent behind help requests
+* Route inputs to appropriate downstream systems (e.g., generators, agents)
+
+---
+
+## 🚀 Version Update (v1 → v2)
+
+### 🔹 v1
+
+* Trained on ~100 examples
+* Limited generalization
+* Struggled with messy or informal input
+
+### 🔹 v2 (Current)
+
+* Trained on **1,000 examples**
+* Balanced dataset across all categories
+* Strong performance on:
+
+  * informal/slang input
+  * mixed tone messages
+  * ambiguous phrasing
+  * real CIC-style check-ins
+
+👉 v2 significantly improves **accuracy, stability, and real-world usability**
+
+---
+
+## 🧩 Task Definition
+
+**Task Type:** Text Classification
+
+**Input:** Student message
+**Output:** One of 5 help categories
+
+---
+
+## 🏷️ Labels
+
+| Label              | Description                                         |
+| ------------------ | --------------------------------------------------- |
+| `learning_help`    | User is trying to understand a concept or skill     |
+| `project_help`     | User needs direction or next steps in a project     |
+| `technical_issue`  | Something is broken or not working                  |
+| `attendance_issue` | User missed a meeting or needs to catch up          |
+| `general_guidance` | User expresses uncertainty, stress, or needs advice |
+
+---
+
+## 🏗️ Model Architecture
+
+* Base Model: distilbert-base-uncased
+* Fine-tuned for sequence classification
+* Number of labels: 5
+
+---
+
+## ⚙️ Training Configuration
+
+* Epochs: 4
+* Learning Rate: 2e-5
+* Batch Size: 8
+* Weight Decay: 0.01
+* Train/Validation Split: 80/10/10
+
+---
+
+## 📊 Training Results
+
+| Epoch | Training Loss | Validation Loss |
+| ----- | ------------- | --------------- |
+| 1     | 0.552         | 0.512           |
+| 2     | 0.111         | 0.122           |
+| 3     | 0.032         | 0.077           |
+| 4     | 0.025         | 0.064           |
+
+---
+
+## 📈 Performance Summary
+
+* **Low validation loss (~0.06)**
+* Strong generalization across unseen inputs
+* Stable convergence during training
+* Handles:
+
+  * messy/slang text
+  * indirect requests
+  * multi-layered inputs
+
+---
 
-## Model description
+## 🧪 Example Predictions
 
-More information needed
+**Input:**
 
-## Intended uses & limitations
+```
+i missed the meeting and now idk what we’re doing
+```
 
-More information needed
+**Output:**
 
-## Training and evaluation data
+```
+attendance_issue
+```
 
-More information needed
+---
+
+**Input:**
+
+```
+my model works but the predictions are weird and I don’t know why
+```
+
+**Output:**
+
+```
+technical_issue
+```
+
+---
+
+**Input:**
+
+```
+I feel like I’m behind and don’t know what to focus on
+```
+
+**Output:**
+
+```
+general_guidance
+```
+
+---
+
+## 🔗 System Integration
+
+This model is integrated into an MCP (Model Context Protocol) system where it acts as:
+
+> **Entry-point classifier for routing student inputs**
+
+Pipeline example:
+
+```
+User Input → Help Classifier → (Future: Generator / Summarizer)
+```
+
+---
+
+## 🎯 Use Cases
+
+* Help request classification
+* Slack/Discord message routing
+* Educational AI assistants
+* CIC ecosystem tools
+* AI agent pipelines
+
+---
+
+## ⚠️ Limitations
+
+* Single-label classification (some messages may contain multiple intents)
+* Edge cases may still overlap between categories
+* Domain-specific (focused on student tech environments)
+
+---
+
+## 🔮 Future Improvements
+
+* Multi-label classification
+* Larger dataset (2,000+ examples)
+* Confidence scoring
+* Integration with response generation models
+* Continuous retraining with real user data
+
+---
+
+## 👤 Author
+
+Created by Kingston Lewis as part of the Coding in Color program for the AI Dev team.
+
+---
+
+# help-classifier-v2
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the King-8/help-request-messages-v2 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0643
 
-## Training procedure
 
 ### Training hyperparameters
 
@@ -44,6 +223,7 @@ The following hyperparameters were used during training:
 - num_epochs: 4
 - mixed_precision_training: Native AMP
 
+
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss |