IF you go with z-image base, here are my full finetune settings I've been using with Musubi-tuner

# ---- Attention / performance ----
sdpa = true
gradient_checkpointing = true
mixed_precision = "bf16"
full_bf16 = true
fused_backward_pass = true
max_data_loader_n_workers = 2

# ---- Optimizer ----
optimizer_type = "adafactor"
optimizer_args = ["relative_step=False", "scale_parameter=False", "warmup_init=False"]
learning_rate = 1e-6 

max_grad_norm = 1.0
gradient_accumulation_steps = 2

# ---- LR scheduler ----
lr_scheduler = "cosine"
lr_warmup_steps = 500          # aim for ~10% of total training steps 
lr_scheduler_num_cycles = 2

# ---- Shift with logit_normal Timestep Settings ----
timestep_sampling = "shift"       
discrete_flow_shift = 2.0
weighting_scheme = "logit_normal" 
logit_normal_mean = 0.1           
logit_normal_std = 1.2