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Upload v5/training_config.toml with huggingface_hub

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  1. v5/training_config.toml +61 -0
v5/training_config.toml ADDED
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+ pretrained_model_name_or_path = "/workspace/models/flux1-dev.safetensors"
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+ ae = "/workspace/models/ae.safetensors"
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+ t5xxl = "/workspace/models/t5xxl_fp16.safetensors"
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+ clip_l = "/workspace/models/clip_l.safetensors"
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+ output_dir = "/workspace/kohya_models/rita-v5"
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+ dataset_repeats = 16
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+ resolution = "512,512"
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+ train_batch_size = 2
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+ network_dim = 16
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+ network_alpha = 16
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+ optimizer_type = "Adamw8bit"
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+ unet_lr = 0.0005
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+ epoch = 12
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+ max_train_steps = 1500
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+ apply_t5_attn_mask = false
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+ cache_latents = true
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+ cache_latents_to_disk = true
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+ cache_text_encoder_outputs = true
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+ cache_text_encoder_outputs_to_disk = true
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+ clip_skip = 1
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+ discrete_flow_shift = 3.1582
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+ full_bf16 = true
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+ mixed_precision = "bf16"
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+ gradient_accumulation_steps = 1
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+ gradient_checkpointing = true
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+ guidance_scale = 1.0
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+ highvram = true
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+ huber_c = 0.1
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+ huber_schedule = "snr"
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+ loss_type = "l2"
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+ lr_scheduler = "cosine_with_restarts"
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+ lr_scheduler_args = []
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+ lr_scheduler_num_cycles = 3
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+ lr_scheduler_power = 1
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+ max_data_loader_n_workers = 0
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+ max_grad_norm = 1
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+ max_timestep = 1000
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+ min_snr_gamma = 5
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+ model_prediction_type = "raw"
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+ network_args = [ "train_double_block_indices=all", "train_single_block_indices=all",]
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+ network_module = "networks.lora_flux"
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+ network_train_unet_only = true
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+ noise_offset = 0.1
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+ noise_offset_type = "Original"
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+ optimizer_args = []
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+ prior_loss_weight = 1
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+ sample_sampler = "euler"
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+ sdpa = true
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+ seed = 42
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+ t5xxl_max_token_length = 512
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+ text_encoder_lr = []
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+ timestep_sampling = "sigmoid"
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+ output_name = "lora"
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+ save_state_to_huggingface = true
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+ save_model_as = "safetensors"
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+ save_every_n_epochs = 1
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+ save_precision = "bf16"
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+ caption_extension = ".txt"
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+ xformers = "sdpa"
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+ enable_bucket = false
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+ dataset_config = "/workspace/kohya_models/rita-v5/dataset_config.json"