LR Warmup-Decay Schedule Issue
LR warmup-decay schedule issues cause training instability at transitions between phases.
LR warmup-decay schedule issues cause training instability at transitions between phases.
What this failure is
LR Warmup-Decay Schedule Issue is a Training Stability failure seen during ML training runs. LR warmup-decay schedule issues cause training instability at transitions between phases. Common tags: Warmup, Decay, Learning Rate, Scheduler.
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Why it happens (the mechanism)
Learning rate changes too quickly at warmup end. Decay rate is too aggressive. Warmup and decay phases overlap incorrectly. Schedule milestones don't match actual training steps. Taken together, these mechanisms explain why the failure is reproducible, why it tends to surface on specific workloads or scales, and why generic mitigation attempts often fall short without addressing the underlying cause.
What you'll observe
- Loss spikes at warmup end
- Loss spikes at decay start
- Training is unstable at schedule transitions
Common symptoms and what they mean
| Symptom | Why it happens |
|---|---|
| Loss jumps at step 1000 (warmup end) | Learning rate changes too quickly at warmup end |
| Loss jumps at step 10000 (decay start) | Decay rate is too aggressive |
| Unstable training in middle epochs | Warmup and decay phases overlap incorrectly |
Which systems are affected
- Transformer training with warmup-decay schedule
- Transfer learning with custom schedule
- Large-scale training with multi-phase schedule
How to confirm this is the problem
Use this checklist to test the hypothesis against a small reproduction. No single line proves the root cause, so preserve the preceding events and compare one variable at a time.
- ✓Reproduce the failure from a clean checkpoint/seed: the symptom must appear without warm-up state from a previous run.
- ✓Verified signal present: Loss jumps at step 1000 (warmup end)
- ✓Verified signal present: Loss jumps at step 10000 (decay start)
- ✓Verified signal present: Unstable training in middle epochs
- ✓A targeted fix from the "How to fix it" section eliminates or substantially reduces the symptom within one validation pass.
The fix and the prevention pattern
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Diagnose this failure in VS Code
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Root cause
- Learning rate changes too quickly at warmup end
- Decay rate is too aggressive
- Warmup and decay phases overlap incorrectly
- Schedule milestones don't match actual training steps
The fix and how to prevent it
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