feat: add eval_r128_candidates.json

Evaluates top 5 adapters from r128_sweet_spot: baseline, lr_5e4_r128,
lr_3e4_r256, lr_3e4_r128, curriculum_lr_3e4 final + step 6000 checkpoint
(before regression) for spectral comparison.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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2026-04-08 17:28:28 +02:00
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{
"name": "eval_r128_candidates",
"description": "Top candidates from r128_sweet_spot. Comparing the two lowest-loss runs, the stable lr=3e-4, and the curriculum run that hit 0.161 before regressing. Baseline included as perceptual reference.",
"data_dir": "/media/unraid/davinci/Selva/BJ/features",
"output_dir": "/media/unraid/davinci/Selva/BJ/evals/r128_candidates",
"steps": 25,
"seed": 42,
"adapters": [
{
"id": "baseline",
"description": "No LoRA — base model output for perceptual reference"
},
{
"id": "lr_5e4_r128",
"description": "Best loss overall (0.137), still descending at step 10k",
"path": "/media/unraid/davinci/Selva/BJ/experiment/r128_sweet_spot/g1_r128_lr_5e4/adapter_final.pt"
},
{
"id": "lr_3e4_r256",
"description": "Tied with lr_5e4 at 0.139, higher rank — does extra capacity help perceptually?",
"path": "/media/unraid/davinci/Selva/BJ/experiment/r128_sweet_spot/g4_r256_lr_3e4/adapter_final.pt"
},
{
"id": "lr_3e4_r128",
"description": "Stable plateau from step 4k to 10k (0.221) — visually confirmed clean spectrograms",
"path": "/media/unraid/davinci/Selva/BJ/experiment/r128_sweet_spot/g1_r128_lr_3e4/adapter_final.pt"
},
{
"id": "curriculum_lr_3e4",
"description": "Best min loss of all (0.161 at step 6k), regressed to 0.193 after curriculum switch — curious if the early checkpoint sounds better",
"path": "/media/unraid/davinci/Selva/BJ/experiment/r128_sweet_spot/g2_r128_lr_3e4_curriculum/adapter_final.pt"
},
{
"id": "curriculum_lr_3e4_step6000",
"description": "Same run at its actual best step (before regression) — compare against adapter_final to hear the regression",
"path": "/media/unraid/davinci/Selva/BJ/experiment/r128_sweet_spot/g2_r128_lr_3e4_curriculum/adapter_step06000.pt"
}
]
}