---
license: apache-2.0
language:
  - en
metrics:
  - accuracy
  - f1
  - precision
  - recall
base_model: FacebookAI/roberta-base
pipeline_tag: text-classification
library_name: transformers
tags:
  - roberta
  - toxicity-detection
  - transformers
  - text-classification
  - custom-dataset
eval_results:
  eval_accuracy: 0.94
  eval_f1: 0.93
  eval_precision: 0.95
  eval_recall: 0.91
---

# 🛡️ Toxicity-RoBERTa-Base

A fine-tuned transformer model built on top of [`roberta-base`](https://huggingface.co/roberta-base) to **detect toxic content** in text — including insults, threats, hate speech, and offensive language.  
The model is lightweight, accurate, and ideal for **real-time moderation** tasks.

---

## 🧩 Use Cases

This model is designed to flag toxic messages in:

- 🧵 Social media comments and posts  
- 🛠️ Developer forums and Discord/Slack bots  
- 🧠 LLM output moderation  
- 🧩 Community Q&A sites (like Reddit, Stack Overflow)  
- 🚨 User-generated content platforms (blogs, review sites, games)

---

## 🔍 Model Summary

| Attribute             | Details                            |
|----------------------|-------------------------------------|
| Base Architecture    | `roberta-base`                      |
| Fine-tuned For       | Toxic vs. Non-toxic classification |
| Classes              | `0 = Non-toxic`, `1 = Toxic`        |
| Language             | English (`en`)                      |
| Data Sources         | Custom dataset (multi-domain)       |
| Framework            | 🤗 Transformers                     |
| Total Parameters     | ~125M                               |

---

## 📊 Performance

| Metric       | Result |
|--------------|--------|
| Accuracy     | 94%    |
| F1 Score     | 93%    |
| Precision    | 95%    |
| Recall       | 91%    |

---

## ⚙️ Quick Start

### 💡 Install Required Libraries

```bash
pip install transformers torch