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Keyword: teacher-student distillation ×Clear all

2 claims from 1 paper

1. Computer Science › Advanced Neural Network Applications

   Training data-efficient image transformers & distillation through attention

   Touvron, Cord, Douze, Massa, Sablayrolles and Jeǵou · arXiv (Cornell University) · 2020

   The authors train a convolution-free image transformer on ImageNet alone in under three days on one computer, and add a transformer-specific distillation method that gives results competitive with convnets.

   Unchecked2 claims
   Show 2 claims

   1. UncheckedA vision transformer with 86 million parameters reaches 83.1% top-1 accuracy on ImageNet, single-crop, using no external training data.“Our reference vision transformer (86M parameters) achieves top-1 accuracy of 83.1% (single-crop evaluation) on ImageNet with no external data.”
   2. UncheckedThe paper's distillation method uses a special distillation token so a student transformer learns from a teacher model through attention.“It relies on a distillation token ensuring that the student learns from the teacher through attention.”