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Related Questions
- Can using a cosine learning rate schedule lead to oscillations or instability in the training process?
- How might a cosine learning rate schedule impact the convergence rate of the model, particularly during the final stages of training?
- Are there any specific scenarios or network architectures where a cosine learning rate schedule is less effective or even counterproductive?
- Can a cosine learning rate schedule cause overfitting or underfitting, and if so, under what conditions?
- How does a cosine learning rate schedule interact with other hyperparameters, such as batch size, number of epochs, or momentum?
- In what ways might a cosine learning rate schedule affect the generalization performance of the model, particularly on out-of-distribution data?
- Are there any known pitfalls or edge cases when implementing a cosine learning rate schedule in practice?
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