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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{
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"name": "eval_r128_candidates",
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"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.",
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"data_dir": "/media/unraid/davinci/Selva/BJ/features",
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"output_dir": "/media/unraid/davinci/Selva/BJ/evals/r128_candidates",
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"steps": 25,
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"seed": 42,
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"adapters": [
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{
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"id": "baseline",
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"description": "No LoRA — base model output for perceptual reference"
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},
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{
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"id": "lr_5e4_r128",
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"description": "Best loss overall (0.137), still descending at step 10k",
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"path": "/media/unraid/davinci/Selva/BJ/experiment/r128_sweet_spot/g1_r128_lr_5e4/adapter_final.pt"
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},
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{
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"id": "lr_3e4_r256",
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"description": "Tied with lr_5e4 at 0.139, higher rank — does extra capacity help perceptually?",
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"path": "/media/unraid/davinci/Selva/BJ/experiment/r128_sweet_spot/g4_r256_lr_3e4/adapter_final.pt"
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},
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{
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"id": "lr_3e4_r128",
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"description": "Stable plateau from step 4k to 10k (0.221) — visually confirmed clean spectrograms",
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"path": "/media/unraid/davinci/Selva/BJ/experiment/r128_sweet_spot/g1_r128_lr_3e4/adapter_final.pt"
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},
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{
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"id": "curriculum_lr_3e4",
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"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",
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"path": "/media/unraid/davinci/Selva/BJ/experiment/r128_sweet_spot/g2_r128_lr_3e4_curriculum/adapter_final.pt"
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},
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{
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"id": "curriculum_lr_3e4_step6000",
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"description": "Same run at its actual best step (before regression) — compare against adapter_final to hear the regression",
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"path": "/media/unraid/davinci/Selva/BJ/experiment/r128_sweet_spot/g2_r128_lr_3e4_curriculum/adapter_step06000.pt"
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}
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]
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}
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