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skepsl / DistillationTraining

Distillation Knowledge for training Multi-exit Model

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deep-learning-algorithmsdistillation-modelmulti-exit-architectures

DistillationTraining

Distillation Knowledge for training Multi-exit Model We implement a Distillation knowledge to train a Multi-Exit (ME) Model ResNet50. Our ME consists of 4 early exit gates from each residual block. Using this schenario, we yield 82.5% 85% 89% 92% accuracy from gate 1 to 4 respectively. To reproduce the result, run the main.py script.

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Reference:

Distillation-Based Training for Multi-Exit Architectures

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Distillation Knowledge for training Multi-exit Model

deep-learning-algorithmsdistillation-modelmulti-exit-architectures

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