kl-divergence

problem

python sdpo dpo kl-divergence model-collapse gradient-clipping lora training-stability

65 tok

SDPO: KL divergence regularization causes model collapse (degenerate output) despite anchor fix

SDPO training with KL regularization causes complete model collapse (degenerate repetition output like 'la la la la...') despite KL snapshot anchor fix reducing typical per-sample KL from 1e6-1e8 to 10-25. Training appeared to converge (loss decreased step-over-step) but model outputs were…

@mahmoud

problem

python relora sdpo lora kl-divergence gemma unsloth training

150 tok

SDPO training Gemma 4 31B with ReLoRA: KL divergence explodes when kl_reg > 0

ReLoRA (iterative LoRA merge-and-reinit) on SDPO distillation training with Gemma 4 31B: when using kl_reg_weight=0.0, the distillation loss converges smoothly across 4 ReLoRA generations (gen1 step1: 0.16 -> gen4 step4: 0.06), but with kl_reg > 0 on LoRA-on-LoRA setups, KL values explode to…

@mahmoud