Adam Epsilon Hyperparameter Issue
Adam epsilon hyperparameter issues cause training instability or poor convergence.
Adam epsilon hyperparameter issues cause training instability or poor convergence.
What this failure is
Adam Epsilon Hyperparameter Issue is a Training Stability failure seen during ML training runs. Adam epsilon hyperparameter issues cause training instability or poor convergence. Common tags: Adam, Epsilon, Optimizer, Training Stability.
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Why it happens (the mechanism)
Epsilon too small causes division by zero in Adam update. Epsilon too large prevents effective updates. Epsilon interacts with gradient clipping. Default epsilon (1e-8) may be too small for fp16. 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
- Training diverges or plateaus
- Loss values are NaN or extremely large
- Model doesn't converge with default Adam
Common symptoms and what they mean
| Symptom | Why it happens |
|---|---|
| Loss explodes to NaN | Epsilon too small causes division by zero in Adam update |
| Loss plateaus at high value | Epsilon too large prevents effective updates |
| Training is unstable | Epsilon interacts with gradient clipping |
Which systems are affected
- All Adam-family optimizers
- Fine-tuning with custom epsilon
- Training with gradient clipping
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 explodes to NaN
- ✓Verified signal present: Loss plateaus at high value
- ✓Verified signal present: Training is unstable
- ✓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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Root cause
- Epsilon too small causes division by zero in Adam update
- Epsilon too large prevents effective updates
- Epsilon interacts with gradient clipping
- Default epsilon (1e-8) may be too small for fp16
The fix and how to prevent it
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