Small Vision Transformers: What the Attention Heads Look At
A small ViT trained on CIFAR-10 learns local attention in layer 1 and global attention in the last layers. The fixes that raise accuracy make it more local.
Lead AI Engineer · Writing since 2016
I write about reinforcement learning, transformers, multi-agent systems, and the tools I build along the way.
A small ViT trained on CIFAR-10 learns local attention in layer 1 and global attention in the last layers. The fixes that raise accuracy make it more local.
A small Vision Transformer starts at 57% on CIFAR-10 and reaches 92.9% after eight fixes. Each fix has a measured gain, and ResNet-18 still wins.
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