Describe the consequences of choosing an initial learning rate (0) that is too low for this system. How would you address these issues, and what tradeoffs would you consider?
Choosing an initial learning rate that is too low can lead to slow convergence or even getting stuck in a local minimum. This can be addressed by increasing the initial learning rate, but it may lead to higher oscillations in the cost function.
What is the most critical hyperparameter to focus on during this limited time, and how would you approach its optimization?
The learning rate has the most significant impact on model performance. I would start by analyzing the current learning rate’s effect on training speed and convergence. If it’s too high, reduce it until the training process becomes stable. Conversely, if it’s too low, increase it cautiously to avoid overshooting.