cleanup 3

example_trainer/README.md

@@ -330,7 +330,6 @@ The trainer supports multiple optimizer options to trade off between speed, memo
 | `adamw` | ~32GB (for 8B model) | Fastest | Full FP32 | None |
 | `adamw_8bit` (default) | ~8GB | Fast | 8-bit quantized | `bitsandbytes` |
 | `adafactor` | ~8GB | Fast | Full (no momentum) | `transformers` |
-| `adamw_cpu` | ~0GB (on CPU) | ~2x slower | Full FP32 | None |
 
 **Usage:**
 ```bash
@@ -342,21 +341,16 @@ The trainer supports multiple optimizer options to trade off between speed, memo
 
 # Adafactor - no momentum states, good for large models
 --optimizer adafactor
-
-# CPU offload - experimental, use when nothing else fits
---optimizer adamw_cpu
 ```
 
 **Recommendations:**
 - **8B models on 80GB:** Use `adamw` (fastest)
 - **14B+ models on 80GB:** Use `adamw_8bit` or `adafactor`
 - **24B models:** Use `adafactor` with reduced batch size
-- **adamw_cpu:** Experimental - not well tested, ~2x slower due to CPU↔GPU transfers
 
 **Potential Risks:**
 - `adamw_8bit`: Quantization may slightly affect convergence in edge cases; generally safe
 - `adafactor`: No momentum can make training slightly less stable; use with larger batch sizes
-- `adamw_cpu`: Significantly slower; only use when you have no other option
 
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