config:
  name: flux_dev_Source_engine_asthetics
  process:
  - datasets:
    - cache_latents_to_disk: true
      caption_dropout_rate: 0.2
      caption_ext: txt
      folder_path: /root/lorahub/flux_dev_Source_engine_asthetics/dataset
      resolution:
      - 512
      - 768
      - 1024
      shuffle_tokens: false
      token_dropout_rate: 0.01
    device: cuda:0
    model:
      is_flux: true
      name_or_path: black-forest-labs/FLUX.1-dev
      quantize: true
      text_encoder_bits: 8
    network:
      linear: 42
      linear_alpha: 42
      transformer_only: true
      type: lora
    performance_log_every: 500
    sample:
      height: 1024
      neg: ''
      prompts:
      - The image shows a cityscape with tall buildings in the background, a tree
        in the middle of a park, a bench, a fence, a pole, and a few other objects,
        [trigger]
      - The image shows a room with a carpeted floor, a table with monitors and other
        objects on it, machines, a wall in the background, and a light at the top.
        It appears to be a control room, with a large machine in the center, [trigger]
      - The image shows a person taking a photo of a forest with their cell phone.
        The person's hand is in the foreground, holding the phone up to capture the
        scene. The background of the image is filled with trees, plants, grass, rocks,
        and a wooden bridge, [trigger]
      - The image shows an abandoned bridge with graffiti on the side of it, surrounded
        by street poles, street lights, grills, trees, and buildings. The sky in the
        background is filled with clouds, [trigger]
      sample_every: 500
      sample_steps: 25
      sampler: flowmatch
      seed: 42
      walk_seed: true
      width: 1024
    save:
      dtype: float16
      max_step_saves_to_keep: 3
      save_every: 500
      save_format: diffusers
    train:
      batch_size: 1
      dtype: bf16
      ema_config:
        ema_decay: 0.99
        use_ema: true
      gradient_accumulation_steps: 1
      gradient_checkpointing: true
      linear_timesteps: true
      loss_type: mse
      lr: 0.0002
      noise_scheduler: flowmatch
      optimizer: adamw8bit
      reg_weight: 1.0
      steps: 3000
      target_noise_multiplier: 1.0
      train_text_encoder: false
      train_unet: true
    training_folder: /root/lorahub
    trigger_word: In the style of the source engine
    type: sd_trainer
job: extension
meta:
  description: ''