metadata

license: apache-2.0
language:
  - it
  - en
pipeline_tag: text-classification

🛡️ Sentinella: Lightweight Content Safety Guardian

🎯 Model Overview

Sentinella is a compact yet powerful content safety classifier designed specifically for Italian language moderation. This model serves as your efficient first line of defense against harmful content.

📊 Key Metrics

Size: 32M parameters
Accuracy: 93% on test set
Max Input Length: 8,192 tokens
Training Data: more than 100,000 balanced examples (harmful/safe)

🔧 Technical Specifications

Base Architecture

Base Model: jinaai/jina-embeddings-v2-small-en
Model Adaptation:
- Enhanced with a custom classifier head using a two-layer architecture
- Optimized dropout rate of 0.1 for regularization
- CLS token pooling strategy for sequence representation
- Implemented with cross-entropy loss for binary classification

Classification Details

Output Labels:
- NEGATIVE (0): Harmful content
- POSITIVE (1): Safe content

💫 Key Features

Lightweight: At just 32M parameters, Sentinella is designed for efficiency
Long Context: Handles up to 8k tokens of input text
High Performance: 93% accuracy in content safety classification
Optimized Architecture: Custom classification head with dimensionality reduction for improved efficiency

🚀 Use Cases

Content moderation for Italian text
Safe content filtering
Automated content screening
Real-time text analysis

🎓 Training Details

Training Dataset: more than 100,000 examples
- Balanced distribution of safe and harmful content
- Focused on Italian language text
Training Strategy:
- Fine-tuned embedding representation
- Intermediate layer dimensionality reduction
- ReLU activation for non-linearity
- Optimized dropout for regularization

📈 Performance Considerations

Optimized for real-time classification
Low memory footprint
Efficient inference time
Suitable for both CPU and GPU deployment

📝 Citation

If you use Sentinella in your research or application, please cite this work as:

@model{sentinella,
  title={Sentinella: Lightweight Italian Content Safety Classifier},
  year={2024},
  publisher={[Michele Montebovi]},
  note={32M parameter content safety model}
}