How can you detect and mitigate vanishing gradients in a deep Transformer network?

Vanishing gradients in deep Transformer networks can be detected by monitoring the magnitude of the gradients during training. If the gradients in the earlier layers of the network are significantly smaller than the gradients in the later layers, it indicates that the gradients are vanishing. This can be monitored using tools like TensorBoard or by logging the gradient norms during training. Another way to detect vanishing gradients is to observe the learning rate adaptation. If the adaptive learning rate methods, like Adam, result in very large learning rates for the i....