Too Hot, Too Cold

A model's training loss oscillates wildly and occasionally spikes upward instead of shrinking. Which learning-rate issue is the most likely cause?

The learning rate has no effect on convergence stability

The learning rate is too high, causing updates to overshoot the minimum

The learning rate is too low, causing updates to overshoot the minimum

The learning rate is exactly optimal for convergence