README.md

---
language: en
license: mit
library_name: transformers
tags:
- text-classification
- pytorch
- distilbert
- customer-support
- nlp
datasets:
- Bitext/customer-support-intent-dataset
metrics:
- accuracy
- f1
pipeline_tag: text-classification
---

# DistilBERT for Automated Tech-Support Classification

This model is a fine-tuned version of **DistilBERT** (`distilbert-base-uncased`) trained to classify customer support tickets into **27 specific intents** across 11 major categories. 

This model is the "Brain" of the **Automated Tech-Support Ticketing System** project.

## 🚀 Model Details
- **Architecture**: DistilBERT (Transformers)
- **Task**: Multi-class Text Classification
- **Intents**: 27 (e.g., `cancel_order`, `recover_password`, `edit_account`, etc.)
- **Framework**: PyTorch & Hugging Face Transformers

## 📊 Performance (Week 2 Results)
The model achieved near-perfect scores on the **Bitext Customer Support Dataset**:
- **Training Accuracy**: 100.00%
- **Validation Accuracy**: 99.76%
- **Macro Average F1-Score**: 1.00

## 📂 Artifacts in this Repo
- `best_model_state.bin`: The trained PyTorch model weights.
- `tokenizer/`: Full configuration for the BERT tokenizer.
- `label_encoder.joblib`: The mapping for the 27 intent classes.

## 🛠️ Integration with Project
This model is designed to be used in conjunction with a FastAPI backend and a Gemini 2.5-flash reasoning layer. 

To use this model in your local setup, you can clone this repository or use the `huggingface_hub` library to download the artifacts into the `models/` directory of the main project.

### How to Load (Example):
```python
from transformers import DistilBertForSequenceClassification, DistilBertTokenizer
import torch

# Path to the downloaded model
model = DistilBertForSequenceClassification.from_pretrained("./models/tokenizer", num_labels=27)
model.load_state_dict(torch.load("./models/best_model_state.bin"))
```

# 🔗 Main Project Repository
For the full end-to-end implementation (FastAPI, Streamlit, and LLM Integration), please visit my GitHub:
👉 [GitHub Repository](https://github.com/Genome06/automated-tech-support-ticketing)

Developed by Baltasar Patrizhard Djata Part of the "Automated Tech-Support Ticketing System" Portfolio Project (2026).