Cyclic LR Scheduler Issues
Cyclic LR scheduler issues arise from incorrect base/max LR, step size, or mode (triangular, triangular2, exp_range).
Cyclic LR scheduler issues arise from incorrect base/max LR, step size, or mode (triangular, triangular2, exp_range).
What this failure is
Cyclic LR Scheduler Issues is a Training Stability failure seen during ML training runs. Cyclic LR scheduler issues arise from incorrect base/max LR, step size, or mode (triangular, triangular2, exp_range). Common tags: Cyclic Lr, Scheduler, Training Stability, Hyperparameter.
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Why it happens (the mechanism)
Step size too small (oscillates too much) or too large (no cycling). Base LR and max LR inverted. Mode not appropriate for task. Gamma decay too aggressive for exp_range. 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
- Cyclic LR training is unstable
- Cyclic LR doesn't improve over constant LR
- Cyclic LR model performs worse
Common symptoms and what they mean
| Symptom | Why it happens |
|---|---|
| Loss spikes at peak LR | Step size too small (oscillates too much) or too large (no cycling) |
| Cyclic LR step size too small or too large | Base LR and max LR inverted |
| Cyclic LR base_lr is too high | Mode not appropriate for task |
Which systems are affected
- Training with CyclicLR for fast convergence
- Cyclic learning rate for transfer learning
- Cyclical learning rate for GANs
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 spikes at peak LR
- ✓Verified signal present: Cyclic LR step size too small or too large
- ✓Verified signal present: Cyclic LR base_lr is too high
- ✓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
- Step size too small (oscillates too much) or too large (no cycling)
- Base LR and max LR inverted
- Mode not appropriate for task
- Gamma decay too aggressive for exp_range
The fix and how to prevent it
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