🛡️ Toxicity-RoBERTa-Base

A fine-tuned transformer model built on top of 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.

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🧩 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)

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🔍 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

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📊 Performance

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

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⚙️ Quick Start

💡 Install Required Libraries

pip install transformers torch