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fix(dspine): correct training objective details - #1004
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Can you help to rebase your code and test it for several epochs? @A-Gentle-Cat |
- Code loss: mean of the per-layer alignment losses. - Last-write refinement: ce_weight x CE averaged over rows whose label lies in the candidate set, plus (1 - ce_weight) x L1 averaged over rows whose candidate mass exceeds candidate_mass_threshold. Both averages are decay-weighted, scaled by the number of supervised rows, and computed per micro-batch. - Normalization: the objective is divided by the number of sequences. - Schedule: the code-loss weight ramps up over the LR warmup; alignment_warmup_steps, when set, fixes the ramp length.
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Rebased and tested with a 1,000-step training run. The results are similar to the previous aligned run. |
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Stacked on #965 (base:
codex/pr942-09-dspine). @jiapingWModifications
I am one of the authors of DSpine. This PR fixes several details of the DSpine training objective:
alignment_warmup_steps, when set, fixes the ramp length).The corresponding recipe change for #967 is proposed as a review suggestion there.
Validation
Open-PerfectBlend with Qwen3-8B, identical recipe and data, one run per configuration, 3,000 steps (about 0.36 epoch):
test_dspine,test_dspine_accumulation,test_dspine_distributed,test_dspine_liger,test_dspine_optimizations,test_builtin_providers,test_ddp_accumulation).