aleleba
363648fb5f
171 steps (901 examples / 16 grad-accum * 3 epochs, ceil-rounded, not the 168 the plan estimated with floor), trained decoupled on spark against the merged bf16 checkpoint that already has LoRA #1 folded in. No OOM, no aborts: train_runtime 24370s (~6h46m, within the ~7.3h projection), eval_loss 0.6306, peak CUDA 74.58GB, trainable% 0.1220 (matches phase 3 exactly). adapter_config.json confirms the guarded hyperparameters: use_rslora and use_dora both false, lora_bias false, modules_to_save null, r=32, lora_alpha=64 -- the combination 20_merge_lora.py's scaling math depends on. Weights never touched the worktree: OUTPUT_DIR was /workspace/ft-models/lora-adapter-penpot on spark (outside the worktree, root-owned by the training container), copied out via `docker exec cat` piped to a non-root file and verified by matching sha256 (79167dfa...) before landing here. Intermediate checkpoint-*/ directories stay on spark; only the final adapter is versioned, same as phase 3's out/lora-adapter/, which this leaves untouched. .gitignore was missing the negation lines for out/lora-adapter-penpot/ despite already documenting that the final adapter should be committed -- added the same two exceptions that out/lora-adapter/ has.
5.1 KiB
base_model, library_name, pipeline_tag, tags
| base_model | library_name | pipeline_tag | tags | |||
|---|---|---|---|---|---|---|
| /workspace/ft-models/Qwen3.6-35B-A3B-mcp-bf16 | peft | text-generation |
|
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