Understanding Transformers Part 9: Stacking Self-Attention Layers

Transformers stack multiple self-attention layers instead of relying only on raw positional-encoded inputs.

Each layer learns its own weights and refines queries, keys, and values to model word relationships more effectively.

This stacked design helps capture richer context in longer or more complex text, improving text encoding.