In the context of learning rate schedules and warm-up strategies, a spike refers to a sudden and temporary increase in the learning rate during training. This rapid change can help accelerate learning by allowing the model to explore different regions of the loss landscape more aggressively, potentially leading to faster convergence. Understanding spikes is crucial for effectively managing how the learning rate evolves throughout the training process.
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