aleleba
52dd307c39
171 steps, train_loss=0.6808, eval_loss=0.6348 (comparable to v1's 0.6306),
peak CUDA memory 74.58GB -- identical to v1's run, confirming the 13
corrective seeds didn't change the memory/length envelope. All guards
verified in adapter_config.json: use_rslora=false, use_dora=false,
lora_bias=false, modules_to_save=null, r=32, lora_alpha=64.
v1 adapter (out/lora-adapter-penpot/, commit 363648f) stays untouched as
a rollback point. New OUTPUT_DIR avoided the overwrite guard.
adapter_model.safetensors sha256 verified identical before/after copying
out of the container (root-owned file, fixed ownership via chown inside
the container since this OUTPUT_DIR landed inside the worktree, unlike
v1's which was copied in from outside).
35 lines
1.1 KiB
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35 lines
1.1 KiB
Plaintext
data/raw/*
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!data/raw/.gitkeep
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!data/raw/replay.jsonl
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!data/raw/sanitized/
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!data/raw/seeds/
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data/raw/.secrets_map.json
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out/*.safetensors
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out/lora-adapter/checkpoint-*/
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*.safetensors
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*.bin
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*.pt
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!out/lora-adapter/adapter_model.safetensors
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!out/lora-adapter/training_args.bin
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!out/lora-adapter-penpot/adapter_model.safetensors
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!out/lora-adapter-penpot/training_args.bin
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!out/lora-adapter-penpot-v2/adapter_model.safetensors
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!out/lora-adapter-penpot-v2/training_args.bin
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__pycache__/
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*.pyc
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.ipynb_checkpoints/
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.env
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.worktrees/
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# Fase 6: checkpoints intermedios del LoRA #2. El adapter final
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# (out/lora-adapter-penpot/adapter_model.safetensors, ~169 MB) SI se commitea, igual que el de
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# la Fase 3; los checkpoint-*/ del Trainer son decenas de GB y viven solo en spark.
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# out/lora-adapter-penpot-v2/ es la iteracion correctiva del paso 6.4.25b (mismo trato).
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out/lora-adapter-penpot/checkpoint-*/
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out/lora-adapter-penpot-v2/checkpoint-*/
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out/*/checkpoint-*/
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# Partes intermedias del corpus de seeds: se concatenan a data/raw/seeds/penpot.jsonl, que es
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# el artefacto versionado. Mantener las partes sueltas invita a editar la copia equivocada.
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data/raw/seeds/_parts/
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