Ethanfel
30127c13ca
Runs a series of BigVGAN fine-tuning experiments from a JSON sweep file. Audio clips loaded once, vocoder deep-copied per experiment, results collected in experiment_summary.json with comparison loss curves. Resume-aware — skips completed experiments on re-run. Includes overnight sweep config (8 experiments): snake alpha steps, GAFilter ablation, phase loss weight, discriminator FM, all_params. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
66 lines
2.3 KiB
JSON
66 lines
2.3 KiB
JSON
{
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"name": "bigvgan_overnight",
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"description": "BigVGAN vocoder quality sweep. Axes: snake_alpha steps, all_params short run, GAFilter on/off, discriminator FM, phase loss weight. All use LoRA-distorted mels as input so vocoder learns to fix LoRA artifacts.",
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"data_dir": "/media/unraid/davinci/Selva/BJ/features",
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"output_root": "/media/unraid/davinci/Selva/BJ/experiment/bigvgan_overnight",
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"base": {
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"train_mode": "snake_alpha_only",
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"steps": 3000,
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"lr": 1e-4,
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"batch_size": 8,
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"segment_seconds": 0.5,
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"lambda_l2sp": 1e-3,
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"use_gafilter": true,
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"gafilter_kernel_size": 9,
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"lambda_phase": 1.0,
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"save_every": 1000,
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"seed": 42,
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"lora_adapter": "/media/unraid/davinci/Selva/BJ/experiment/pissa_sweep/standard_baseline/adapter_final.pt"
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},
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"experiments": [
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{
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"id": "snake_3k_baseline",
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"description": "Snake alpha + GAFilter baseline. 3000 steps, same as first successful run but longer."
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},
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{
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"id": "snake_5k",
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"description": "Snake alpha + GAFilter, 5000 steps. Test if longer training improves further.",
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"steps": 5000
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},
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{
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"id": "snake_no_gafilter",
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"description": "Snake alpha only, no GAFilter. Isolate GAFilter contribution.",
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"use_gafilter": false
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},
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{
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"id": "snake_no_phase",
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"description": "Snake alpha + GAFilter, no phase loss. Isolate phase loss contribution.",
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"lambda_phase": 0.0
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},
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{
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"id": "snake_phase_2",
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"description": "Snake alpha + GAFilter, phase weight 2.0. Stronger phase penalty.",
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"lambda_phase": 2.0
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},
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{
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"id": "snake_lr5e-5",
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"description": "Snake alpha + GAFilter, lower LR 5e-5. Test if slower converges better.",
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"lr": 5e-5,
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"steps": 5000
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},
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{
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"id": "snake_disc_fm",
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"description": "Snake alpha + GAFilter + discriminator feature matching. Perceptual loss should directly penalize harmonic smearing.",
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"discriminator_path": "/media/unraid/davinci/Selva/BJ/experiment/bigvgan_discriminator_optimizer.pt"
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},
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{
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"id": "all_2k_l2sp1e-2",
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"description": "All params, 2000 steps, strong L2-SP (1e-2). Test if full param tuning with heavy anchor beats snake-only.",
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"train_mode": "all_params",
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"steps": 2000,
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"lr": 1e-5,
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"lambda_l2sp": 1e-2
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}
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]
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}
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