Common attention patterns you'll see:
- Diagonal: Each position attends to itself or adjacent positions
- Vertical stripes: Many positions attend to specific important tokens
- Block patterns: Tokens within phrases attend to each other
- Sparse: Most weights near zero, few strong connections
These patterns help interpret what the model learns. Fine-tuning can change these patterns for your domain.