🛡️ SpamVision BETO - Spanish SMS Spam Detector
📖 Model Description
SpamVision BETO is a fine-tuned BERT model for Spanish language specifically designed to detect spam SMS messages with high accuracy. Built on top of the BETO (BERT trained on Spanish corpus), this model achieves 96.2% accuracy in distinguishing between legitimate messages and spam.
This model is part of the SpamVision project, a hybrid AI system that combines rule-based filtering (AFD) with deep learning for maximum spam detection performance.
Key Features
- 🎯 High Accuracy: 96.2% on test dataset
- ⚡ Fast Inference: < 200ms per message
- 🇪🇸 Spanish-optimized: Fine-tuned on Spanish SMS data
- 📱 SMS-focused: Optimized for short messages (< 160 characters)
- 🔄 Production-ready: Used in real-world mobile app
Model Architecture
- Base Model:
dccuchile/bert-base-spanish-wwm-cased - Parameters: ~110M
- Layers: 12 transformer encoder layers
- Hidden Size: 768
- Max Sequence Length: 128 tokens
- Vocabulary Size: 31,002 tokens
🚀 Quick Start
Installation
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Base model
dccuchile/bert-base-spanish-wwm-casedDataset used to train JavicR22/SpamVision
Evaluation results
- Accuracy on Spanish SMS Spam Detectionself-reported0.962
- F1 Score on Spanish SMS Spam Detectionself-reported0.951
- Precision on Spanish SMS Spam Detectionself-reported0.948
- Recall on Spanish SMS Spam Detectionself-reported0.955