{
  "name": "lora_optimized_dataset",
  "description": "LoRA training on optimized dataset (134 clips: resampled 44.1kHz, LUFS-normalized, spectral matched, HF smoothed, gain-augmented). Tests latent augmentation and schedule variants on top of known-best config (PiSSA, rank=128, lr=3e-4).",
  "data_dir": "/media/unraid/davinci/Selva/BJ/features_v2_improved/",
  "output_root": "/media/unraid/davinci/Selva/BJ/experiment/lora_optimized_dataset",
  "base": {
    "rank": 128,
    "lr": 3e-4,
    "steps": 5000,
    "batch_size": 4,
    "warmup_steps": 100,
    "save_every": 1000,
    "seed": 42,
    "init_mode": "pissa",
    "use_rslora": true,
    "target": "attn.qkv",
    "timestep_mode": "uniform",
    "lr_schedule": "constant"
  },
  "experiments": [
    {
      "id": "baseline",
      "description": "Control: known-best config (PiSSA r128 lr=3e-4) on the optimized dataset. No latent augmentation."
    },
    {
      "id": "latent_mixup",
      "description": "Latent mixup alpha=0.4 (MusicLDM). Tests if mixing training latents reduces memorization on 134 clips.",
      "latent_mixup_alpha": 0.4
    },
    {
      "id": "latent_noise",
      "description": "Latent noise sigma=0.02. Mild Gaussian noise on training latents for regularization.",
      "latent_noise_sigma": 0.02
    },
    {
      "id": "mixup_and_noise",
      "description": "Both latent mixup (0.4) and noise (0.02). Combined regularization.",
      "latent_mixup_alpha": 0.4,
      "latent_noise_sigma": 0.02
    },
    {
      "id": "cosine_schedule",
      "description": "Cosine LR decay. lr=3e-4 was stable with constant, but cosine may extract more from 5k steps.",
      "lr_schedule": "cosine"
    },
    {
      "id": "cosine_mixup",
      "description": "Cosine LR + latent mixup. Best regularization combo candidate.",
      "lr_schedule": "cosine",
      "latent_mixup_alpha": 0.4
    },
    {
      "id": "logit_normal",
      "description": "Logit-normal timestep sampling (sigma=1.0). Concentrates training near t=0.5 where flow matching is hardest.",
      "timestep_mode": "logit_normal"
    },
    {
      "id": "curriculum_mixup",
      "description": "Curriculum timesteps (logit_normal first 60%, then uniform) + latent mixup. Full regularization stack.",
      "timestep_mode": "curriculum",
      "latent_mixup_alpha": 0.4
    }
  ]
}