ckpt-cdnoise

Evolution-Strategies fine-tuning checkpoints from IBM Blue Vela.

iter<N>.pth are the periodic training checkpoints and final/pytorch_model.pth is the end-of-run save. The two are NOT copies of each other even at the same N -- the final save is written a few ES steps after the last periodic one, measured at a relative L2 difference of 0.002 to 0.004 where ten iterations move 0.008. Treat final/ as the canonical end-of-run weights.

One copy per iteration is published. Where a run has both a final save and a periodic checkpoint at that same iteration, only the final save is here. Periodic checkpoints at earlier iterations are kept, and a run that never reached its end keeps every periodic checkpoint it has.

All .pth are bf16 state dicts keyed by vLLM parameter names (fused qkv_proj, gate_up_proj), loadable by the trainer resume path.

run	base model	final iteration	periodic checkpoints
cdnoise-dropout-bimodal	Qwen/Qwen2.5-7B-Instruct	500	none
cdnoise-dropout-gauss	Qwen/Qwen2.5-7B-Instruct	500	none
cdnoise-dropout-gauss-fix150	Qwen/Qwen2.5-7B-Instruct	300	none
cdnoise-dropout-unif	Qwen/Qwen2.5-7B-Instruct	500	none
cdnoise-dropout25	Qwen/Qwen2.5-7B-Instruct	500	none
cdnoise-dropout5	Qwen/Qwen2.5-7B-Instruct	500	none
cdnoise-dropout8	Qwen/Qwen2.5-7B-Instruct	500	none
cdnoise-dropout8-fix150	Qwen/Qwen2.5-7B-Instruct	300	none
cdnoise-flip1	Qwen/Qwen2.5-7B-Instruct	500	none
cdnoise-flip10	Qwen/Qwen2.5-7B-Instruct	500	none
cdnoise-flip25	Qwen/Qwen2.5-7B-Instruct	500	none
cdnoise-flip4	Qwen/Qwen2.5-7B-Instruct	500	none
cdnoise-flip5	Qwen/Qwen2.5-7B-Instruct	500	none
cdnoise-flip5-fix150	Qwen/Qwen2.5-7B-Instruct	300	none
cdnoise-flip667	Qwen/Qwen2.5-7B-Instruct	500	none
cdnoise-flip8	Qwen/Qwen2.5-7B-Instruct	500	none
cdnoise-flip8-fix150	Qwen/Qwen2.5-7B-Instruct	300	none
cdnoise-l0-dropout5	Qwen/Qwen2.5-7B-Instruct	500	none
cdnoise-l0-flip5	Qwen/Qwen2.5-7B-Instruct	500	none
cdnoise-l0-region60-80	Qwen/Qwen2.5-7B-Instruct	500	none
cdnoise-region60-80	Qwen/Qwen2.5-7B-Instruct	500	none