Step 400 check: Mac -13.4 % vs GPU -35.0 %; next GPU run bf16 mixed with stage 2; findings in STATE and roadmap
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
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@@ -105,3 +105,18 @@ Training runs on HF Jobs with Unsloth, not on the Mac. No `mlx_lm` training.
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on Mac) is not equal. The overfit test (one document) passed, so key names, transpose and scale are right.
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- Open: decide what to do. Options: (a) accept the base mismatch and train further; (b) train on a higher-precision base (bf16 LoRA,
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larger GPU) so the Mac conversion matches; (c) evaluate on the GPU with the MLX-equivalent base.
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## Findings and next GPU run (2026-10-05)
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| Step | GPU valid loss (nf4 base) | GPU drop | Mac valid loss (MLX 4-bit, converted adapter) | Mac drop |
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|---|---|---|---|---|
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| 0 / base | 0.9228 | | 0.849 | |
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| 200 | 0.6830 | -26.0 % | 0.758 | -10.7 % |
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| 400 | 0.6003 | -35.0 % | 0.735 | -13.4 % |
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- Step 400 Mac log: `runs/stage1/full_step400_valid_loss.log`. The Mac drop grows with the steps (-10.7 % to -13.4 %), but stays far below the GPU drop.
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- Converter `train/peft_to_mlx.py` is proven (overfit test: Mac -98.5 %, GPU -99.97 %). The gap is the base mismatch: an nf4 adapter does not transfer well to the MLX 4-bit base.
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- Decisions (Kral, 2026-10-05): no more GPU runs now. Stage 1 is not trained alone. The stage 1 corpus is mixed with the stage 2 trajectories in one bf16 LoRA run later. The next GPU run uses a bf16 base (no nf4). A bf16 memory test is needed before it (27B bf16 weights are about 54 GB; check GPU size, sequence length 16384, gradient checkpointing).
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- Tool names stay as in the EPOD ABAP MCP server (generic_v0 not used). The ADT "save failed" response cannot be fixed on the server side; the proxy adds a syntax check instead.
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- HF cleanup done: test, overfit and full adapter repos deleted (step 200 and 400 checkpoints too). Kept: dataset `erhankeseli/abap-stage1-data`. Local adapter folders and `data_overfit` deleted.
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- `BUDGET_LIMIT_USD` = 161 (ledger 66.97 + 35 usage x 2.7), until 12 October.
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