Freezing Layers of Your Deep Learning Model — the proper way of doing it

Freezing Layers of a Deep Learning Model — the proper way

ADAM optimizer example in PyTorch

Introduction

It is often useful to freeze some of the parameters for example when you are fine-tuning your model and want to freeze some layers depending on the example you process like illustrated

As we can see for the first example we are freezing the first two layers, and updating the parameters of the …

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