ComfyUI-SelVA/experiments/tier1_thorough.json

{
  "name": "tier1_thorough",
  "description": "Full overnight Tier 1 ablation on 49-clip BJ dataset. 4 groups: rank, alpha, regularisation, and best combinations. ~10-12h depending on GPU.",
  "data_dir": "/media/unraid/davinci/Selva/BJ/features",
  "output_root": "/media/unraid/davinci/Selva/BJ/experiment/tier1_thorough",
  "base": {
    "steps": 4000,
    "rank": 16,
    "alpha": 0.0,
    "lr": 1e-4,
    "batch_size": 16,
    "warmup_steps": 100,
    "grad_accum": 1,
    "save_every": 1000,
    "seed": 42,
    "target": "attn.qkv",
    "timestep_mode": "uniform",
    "logit_normal_sigma": 1.0,
    "curriculum_switch": 0.6,
    "lora_dropout": 0.0,
    "lora_plus_ratio": 1.0
  },
  "experiments": [
    {
      "id": "g1_rank_16",
      "group": "rank",
      "description": "Rank 16 baseline — reference point for all groups."
    },
    {
      "id": "g1_rank_32",
      "group": "rank",
      "description": "Rank 32 — midpoint. Does doubling rank improve quality without overfitting?",
      "rank": 32
    },
    {
      "id": "g1_rank_64",
      "group": "rank",
      "description": "Rank 64 — MMAudio LoRA guide default. Maximum expressiveness at 49 clips.",
      "rank": 64
    },
    {
      "id": "g2_alpha_half_r16",
      "group": "alpha",
      "description": "Alpha=8 with rank 16 (scale=0.5). Reduces intruder singular dimensions (arXiv:2410.21228).",
      "alpha": 8.0
    },
    {
      "id": "g2_alpha_half_r64",
      "group": "alpha",
      "description": "Alpha=32 with rank 64 (scale=0.5). Best-practice scaling for high-rank adapters.",
      "rank": 64,
      "alpha": 32.0
    },
    {
      "id": "g3_lora_plus_4",
      "group": "regularisation",
      "description": "LoRA+ ratio=4 — conservative asymmetric LR. Lower bound for the technique.",
      "lora_plus_ratio": 4.0
    },
    {
      "id": "g3_lora_plus_16",
      "group": "regularisation",
      "description": "LoRA+ ratio=16 — standard from FLUX LoRA literature. Faster early convergence.",
      "lora_plus_ratio": 16.0
    },
    {
      "id": "g3_dropout_0.05",
      "group": "regularisation",
      "description": "LoRA dropout 0.05 only. Light sparsity regularisation (arXiv:2404.09610).",
      "lora_dropout": 0.05
    },
    {
      "id": "g3_dropout_0.1",
      "group": "regularisation",
      "description": "LoRA dropout 0.1 only. Stronger regularisation — may prevent overfitting past step 2000.",
      "lora_dropout": 0.1
    },
    {
      "id": "g3_curriculum",
      "group": "regularisation",
      "description": "Curriculum sampling only: logit_normal steps 1-2400, then uniform (arXiv:2603.12517).",
      "timestep_mode": "curriculum"
    },
    {
      "id": "g4_full_r16",
      "group": "combined",
      "description": "All Tier 1 at rank 16: LoRA+ 16 + dropout 0.05 + curriculum.",
      "lora_plus_ratio": 16.0,
      "lora_dropout": 0.05,
      "timestep_mode": "curriculum"
    },
    {
      "id": "g4_full_r64",
      "group": "combined",
      "description": "All Tier 1 at rank 64 + alpha=32. Best expressiveness + best regularisation.",
      "rank": 64,
      "alpha": 32.0,
      "lora_plus_ratio": 16.0,
      "lora_dropout": 0.05,
      "timestep_mode": "curriculum"
    },

    {
      "id": "g5_lr_low",
      "group": "lr",
      "description": "LR=3e-5 — 3× lower than baseline. Tests if 1e-4 is overshooting.",
      "lr": 3e-5
    },
    {
      "id": "g5_lr_high",
      "group": "lr",
      "description": "LR=3e-4 — 3× higher than baseline. Tests if 1e-4 is too conservative.",
      "lr": 3e-4
    },

    {
      "id": "g6_target_full_r16",
      "group": "target",
      "description": "Rank 16 targeting attn.qkv + linear1 (FFN projections). Doubles LoRA coverage.",
      "target": "attn.qkv linear1"
    },
    {
      "id": "g6_target_full_r64",
      "group": "target",
      "description": "Rank 64 + alpha=32 targeting attn.qkv + linear1. Maximum coverage + expressiveness.",
      "rank": 64,
      "alpha": 32.0,
      "target": "attn.qkv linear1"
    },

    {
      "id": "g4_full_r64_6k",
      "group": "combined",
      "description": "All Tier 1 at rank 64 + alpha=32, extended to 6000 steps. Checks if convergence is done at 4000.",
      "rank": 64,
      "alpha": 32.0,
      "lora_plus_ratio": 16.0,
      "lora_dropout": 0.05,
      "timestep_mode": "curriculum",
      "steps": 6000,
      "save_every": 1000
    }
  ]
}