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Phase Transition Frequency as a Training Time Predictor of Test Accuracy in ResNets

J, Arunan
arXiv (All) · Papers
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artificial-intelligencemachine-learning
The number of discrete class-separability jumps observed during ResNet finetuning is examined empirically as a predictor of final test accuracy. Across 75 experiments spanning four benchmarks (CIFAR-10, CIFAR-100, TinyImageNet, and CIFAR-10-C) and three architectures (ResNet-18, ResNet-50, and ResNe
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