Loss spikes the moment warmup ends: which hyperparameter is the prime suspect?

**Peak learning rate** is the prime suspect. Warmup ramps the effective LR from zero up to a peak over the first few hundred steps. While that ramp is in progress, the effective rate is small, so even a wildly oversized peak feels safe. The moment warmup finishes, the optimizer hands the full peak rate to the parameter updates. If that peak is too large for the regime you are in, the updates take steps too big for the local loss surface. The parameters jump out of the basin they were sitting in, the optimizer momentum points in a stale direction, and the loss spikes and never recovers. The usual root cause is copying a learning rate from a different recipe. Full fine-tuning, LoRA, and DPO all sit at different safe ranges, and a default that works in one breaks the others. The first fix is to halve the peak learning rate and rerun. If the spike disappears, sweep down from there to find the largest stable value. Lengthening warmup may delay the spike, but it does not fix the underlying mismatch.

**Peak learning rate is too high** for the regime. The signature is exactly what was described: clean training through warmup, then a sharp loss spike the instant the schedule reaches its plateau. The mechanism is straightforward. During warmup the effective LR is a small fraction of the configured peak, so updates are gentle and the loss declines smoothly. The schedule hands control to the peak rate at the end of warmup, and that peak is what the run actually trains under from then on. If the peak is calibrated for a different regime, the first full-strength step takes parameters out of their current basin. The usual cause is a mis-anchored default. Full fine-tune LRs of 1e-5 to 5e-5 are far too small for LoRA, which often wants 1e-4 to 5e-4. Conversely, a LoRA-scale 5e-4 dropped into a full fine-tune blows up. DPO and other preference-tuning losses are even more sensitive, with safe peaks closer to 5e-6. First remediation: halve the peak learning rate and rerun for a few hundred steps past the previous spike point. If the spike is gone, sweep downward to find the largest stable value. Lengthening warmup is a useful secondary mitigation but does not fix a mis-scaled peak.