Transcription of Training data-efficient image transformers & distillation ...
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Training data-efficient image transformers & distillation ...
Training data-efficient image transformers & distillation through attentionHugo Touvron?, Matthieu Cord Matthijs Douze?Francisco Massa?Alexandre Sablayrolles?Herv e J egou??Facebook AI Sorbonne UniversityAbstractRecently, neural networks purely based on attention were shown to ad-dress image understanding tasks such as image classification. These high-performing vision transformers are pre-trained with hundreds of millionsof images using a large infrastructure, thereby limiting their this work, we produce competitive convolution-free transformers bytraining on Imagenet only. We train them on a single computer in less than3 days.
Our two new models DeiT-S and DeiT-Ti have fewer param-eters and can be seen as the counterpart of ResNet-50 and ResNet-18. •We introduce a new distillation procedure based on a distillation token, which plays the same role as the class token, except that it aims at re-producing the label estimated by the teacher. Both tokens interact in the
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