Optimizer State Memory
Optimizer state memory (Adam: 2x model size, AdamW: 2x) can exceed model size memory, dominating total usage.
Optimizer state memory (Adam: 2x model size, AdamW: 2x) can exceed model size memory, dominating total usage.
What this failure is
Optimizer State Memory is a Memory failure seen during ML training runs. Optimizer state memory (Adam: 2x model size, AdamW: 2x) can exceed model size memory, dominating total usage. Common tags: Optimizer, Adam, Adamw, State.
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Why it happens (the mechanism)
Adam stores 2x model size (m and v). FP32 master weights for mixed precision. Gradient accumulation adds to state. Optimizer state not offloaded. 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
- Memory usage much higher than model size
- Adam training OOM despite small model
- Optimizer state uses more memory than expected
Common symptoms and what they mean
| Symptom | Why it happens |
|---|---|
| Adam optimizer memory is 2x model size | Adam stores 2x model size (m and v) |
| AdamW with weight decay adds to state | FP32 master weights for mixed precision |
| Mixed precision optimizer state with FP32 master weights | Gradient accumulation adds to state |
Which systems are affected
- AdamW training
- Large model training
- Mixed precision training
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: Adam optimizer memory is 2x model size
- ✓Verified signal present: AdamW with weight decay adds to state
- ✓Verified signal present: Mixed precision optimizer state with FP32 master weights
- ✓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
- Adam stores 2x model size (m and v)
- FP32 master weights for mixed precision
- Gradient accumulation adds to state
- Optimizer state not offloaded
The fix and how to prevent it
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