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configs/train_low.toml

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+# Wan 2.2 I2V 14B - LOW NOISE LoRA training
+# Low noise model handles details, anatomy, fine textures
+
+output_dir = '/home/u/work/output_low'
+dataset = '/home/u/work/diffusion-pipe/configs/dataset_blink.toml'
+
+# training settings
+epochs = 1000
+max_steps = 20000
+micro_batch_size_per_gpu = 2
+pipeline_stages = 1
+gradient_accumulation_steps = 1
+gradient_clipping = 1.0
+warmup_steps = 100
+
+# eval settings
+eval_every_n_epochs = 1
+eval_before_first_step = true
+eval_micro_batch_size_per_gpu = 1
+eval_gradient_accumulation_steps = 1
+
+# misc settings
+save_every_n_steps = 500
+checkpoint_every_n_minutes = 60
+activation_checkpointing = true
+compile = true
+partition_method = 'parameters'
+save_dtype = 'bfloat16'
+caching_batch_size = 1
+steps_per_print = 1
+video_clip_mode = 'single_beginning'
+
+[model]
+type = 'wan'
+ckpt_path = '/home/u/work/models/Wan2.2-I2V-A14B'
+transformer_path = '/home/u/work/models/comfyui/split_files/diffusion_models/wan2.2_i2v_low_noise_14B_fp16.safetensors'
+llm_path = '/home/u/work/models/comfyui/split_files/text_encoders/umt5_xxl_fp16.safetensors'
+dtype = 'bfloat16'
+transformer_dtype = 'float8'
+timestep_sample_method = 'logit_normal'
+# Full timestep range for low noise — helps with high->low switching at inference
+# (advice from PENISLORA author: train low on 0-1 instead of restricted range)
+
+[adapter]
+type = 'lora'
+rank = 16
+dtype = 'bfloat16'
+
+[optimizer]
+type = 'adamw_optimi'
+lr = 2e-5
+betas = [0.9, 0.99]
+weight_decay = 0.01
+eps = 1e-8