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.

🧩 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

pip install transformers torch

raghavv2710/toxicity-roberta-base

🛡️ Toxicity-RoBERTa-Base

🧩 Use Cases

🔍 Model Summary

📊 Performance

⚙️ Quick Start

💡 Install Required Libraries

raghavv2710/
toxicity-roberta-base