Gradient clipping keeps neural networks stable
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Gradient clipping keeps neural networks stable
Gradient clipping is a crucial technique used to stabilize the training of deep or recurrent neural networks. During backpropagation, gradients can sometimes grow uncontrollably large—a problem known as exploding gradients. When this happens, the model’s weights change too drastically, causing instability and divergence. Gradient clipping ...
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