| --- |
| title: Toxic Comment Classifier & Explainer |
| emoji: 🧪 |
| colorFrom: indigo |
| colorTo: gray |
| sdk: gradio |
| sdk_version: 4.44.1 |
| python_version: "3.10" |
| app_file: app.py |
| pinned: true |
| license: mit |
|
|
| |
| description: > |
| A multi-label transformer-based Toxic Comment Classifier trained on the Jigsaw dataset. |
| It includes an explainability module (Captum Integrated Gradients) that visualizes |
| which words contribute most to each toxic label, powered by Gradio UI. |
| tags: |
| - text-classification |
| - multi-label |
| - explainable-ai |
| - transformers |
| - gradio |
| - distilbert |
| - nlp |
| - toxicity-detection |
| - huggingface-space |
| --- |
| |
| # 🧠 Toxic Comment Classification — Explainable Multi-Label NLP Model |
|
|
| <p align="center"> |
| <img src="banner.png" alt="Toxic Comment Classification Banner" width="100%"> |
| </p> |
|
|
| <p align="center"> |
| <b>DistilBERT-based multi-label classifier for detecting toxic online comments with explainability powered by Captum Integrated Gradients (IG).</b> |
| </p> |
|
|
| --- |
|
|
| ## 🚀 Overview |
|
|
| This project presents an **explainable AI system** for identifying toxic comments in text, built using a fine-tuned Transformer model (DistilBERT). |
| It performs **multi-label classification** across six toxicity categories while offering **token-level explanations** for each prediction. |
|
|
| ### 🧩 Labels |
| - toxic |
| - severe_toxic |
| - obscene |
| - threat |
| - insult |
| - identity_hate |
|
|
| ### 🎯 Objectives |
| - Fine-tune DistilBERT for robust multi-label toxicity detection |
| - Enhance interpretability using **Captum Integrated Gradients** |
| - Deploy a real-time, user-friendly **Gradio interface** |
|
|
| --- |
|
|
| ## 🧪 How to Use the Demo |
|
|
| 1. Type or paste any comment in the text box |
| 2. Click **“Classify”** to view per-label probabilities and predictions |
| 3. Open the **“Explain”** tab → select a target label |
| 4. Generate a heatmap showing which words **support (red)** or **oppose (blue)** the decision |
|
|
| --- |
|
|
| ## 🧠 Example Inputs |
|
|
| | Example | Expected Labels | |
| |----------|------------------| |
| | “You are a complete idiot.” | toxic / insult | |
| | “I will kill you tomorrow.” | threat / toxic | |
| | “Thanks for your help today!” | non-toxic | |
| | “Go away, you people don’t belong here.” | identity_hate / insult | |
| |
| --- |
| |
| ## ⚙️ Technical Stack |
| |
| | Component | Technology | |
| |------------|-------------| |
| | **Language Model** | DistilBERT (`distilbert-base-uncased`) | |
| | **Frameworks** | PyTorch • Transformers • Gradio | |
| | **Explainability** | Captum (Integrated Gradients) | |
| | **Training** | Stratified splits • Early Stopping • Regularization | |
| | **Visualization** | Gradio UI + Captum HTML heatmaps | |
| | **Deployment** | Hugging Face Spaces | |
| |
| --- |
| |
| ## 📂 Project Structure |
| |
| ``` |
| . |
| ├── app.py # Gradio app entry point |
| ├── requirements.txt # Runtime dependencies |
| ├── artifacts/ |
| │ ├── best/ # Fine-tuned model weights + tokenizer |
| │ └── thresholds.json # Tuned thresholds for each label |
| └── README.md # (this file) |
| ``` |
| |
| --- |
| |
| ## 📊 Model Training Summary |
| |
| - Dataset: [Jigsaw Toxic Comment Classification Challenge](https://www.kaggle.com/datasets/julian3833/jigsaw-toxic-comment-classification-challenge) |
| - Tokenization: DistilBERT (max length = 256) |
| - Loss: Binary Cross-Entropy with Logits (BCEWithLogitsLoss) |
| - Optimizer: AdamW (learning rate = 2e-5, weight decay = 0.02) |
| - Regularization: Dropout (head=0.5, encoder=0.2) |
| - Evaluation Metrics: Macro F1 • Precision • Recall • AUC |
| - Explainability: Captum Layer Integrated Gradients (LIG) |
| |
| --- |
| |
| ## 🖥️ Live Demo |
| |
| > 🚀 Try the interactive demo on Hugging Face Spaces: |
| > 🔗 **[yaekobB / Toxic-Comment-Classification](https://huggingface.co/spaces/yaekobB/Toxic-Comment-Classification)** |
| |
| --- |
| |
| ## 🧰 Dependencies |
| |
| ```txt |
| transformers>=4.41.0 |
| torch>=2.2.0 |
| safetensors>=0.4.2 |
| gradio>=4.20.0 |
| captum>=0.7.0 |
| pandas>=2.0.0 |
| numpy>=1.24.0 |
| ``` |
| |
| --- |
| |
| --- |
| |
| ## 🪪 License |
| |
| This project is licensed under the **MIT License**. |
| You are free to use, modify, and distribute this work with attribution. |
| |
| --- |
| |
| <p align="center"> |
| <i>“Building safer and explainable AI for online interactions.”</i> |
| </p> |
| |
