- Added batch_size VRAM table and updated step recommendations for batched training
- Added adapter strength section with practical guidance (0.6-0.7 for noise)
- Added ComfyUI node as Option A for training (not just CLI)
- Noted .mp3 as not recommended, soundfile fallback implied
- Added output files section with sample_*.wav and loss curve PNGs
- Added "LoRA has no effect" troubleshooting (wrong node wired)
- Updated loss convergence targets based on observed training runs
- Clarified linear1 target: 150+ clips recommended
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Replaces single-sample steps with batched sampling via random.choices().
Tensors are stacked to [B, T, C] before the forward pass; t is now [B].
Default grad_accum lowered to 1 since real batching gives stable gradients.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
500 warmup steps is 25% of a 2000-step run — too long. 100 steps lets
the full lr kick in much earlier without sacrificing stability.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Step checkpoints now save optimizer state, scheduler state, and step
number alongside the LoRA weights. Pass --resume path/to/adapter_stepXXXXX.pt
to continue training from that checkpoint. --steps always means total steps,
so resuming from 1000 with --steps 2000 trains 1000 more steps.
adapter_final.pt format is unchanged (state_dict + meta only) so
SelvaLoraLoader remains compatible.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>