run_id: 1008_qwenLfm_briage
run_root_dir: ./results/Checkpoints
seed: 42
trackers:
- jsonl
- wandb
wandb_entity: jinhuiye
wandb_project: InternM1
is_debug: false
framework:
  name: QwenGR00T
  qwenvl:
    base_vlm: StarVLA/Qwen2.5-VL-3B-Instruct-Action
    attn_implementation: flash_attention_2
    vl_hidden_dim: 2048
  dino:
    dino_backbone: dinov2_vits14
  action_model:
    action_model_type: DiT-L
    hidden_size: 1024
    add_pos_embed: true
    max_seq_len: 1024
    action_dim: 7
    state_dim: 7
    future_action_window_size: 15
    action_horizon: 16
    past_action_window_size: 0
    repeated_diffusion_steps: 8
    noise_beta_alpha: 1.5
    noise_beta_beta: 1.0
    noise_s: 0.999
    num_timestep_buckets: 1000
    num_inference_timesteps: 4
    num_target_vision_tokens: 32
    diffusion_model_cfg:
      cross_attention_dim: 2048
      dropout: 0.2
      final_dropout: true
      interleave_self_attention: true
      norm_type: ada_norm
      num_layers: 16
      output_dim: 1024
      positional_embeddings: null
    action_hidden_dim: 2048
datasets:
  vlm_data:
    dataset_py: vlm_datasets
    dataformat: llava_json
    dataset_use: aokvqa_cauldron_llava_format,sharegpt4v_coco,sharegpt4v_knowledge,sharegpt4v_llava,sharegpt4v_sam,asv2_conversation_en,asv2_detailed_description_en,asv2_region_captioning_en,coco_internvl_longcap_en,coco_karpathy_train_567_en,coco_negative_gpt4o_en,coco_poetry_zh,coco_rem_en_zh,cocorem_exist_yorn_en,cocotextv2_en,cocotextv2_gpt4o_en,okvqa_en,refcoco_grounding_aug_en,refcoco_grounding_en,tallyqa_coco_en,toloka_grounding_aug_en,vqav2_en,vsr_en
    eval_dataset: aokvqa_cauldron_llava_format
    data_flatten: false
    base_interval: 2
    max_pixels: 50176
    min_pixels: 784
    model_max_length: 2048
    model_type: qwen2.5vl
    per_device_batch_size: 3
  vla_data:
    dataset_py: lerobot_datasets
    data_root_dir: playground/Datasets/OXE_LEROBOT
    data_mix: bridge
    action_type: delta_ee
    CoT_prompt: Your task is {instruction}. To identify the key objects for your task.
      Locate their bounding boxes in [x1,y1,x2,y2] format.
    CoT_answer: bbox
    default_image_resolution:
    - 3
    - 224
    - 224
    per_device_batch_size: 16
    load_all_data_for_training: true
    obs:
    - image_0
    image_size:
    - 224
    - 224
trainer:
  epochs: 100
  max_train_steps: 100000
  num_warmup_steps: 10000
  save_interval: 5000
  eval_interval: 1000
  learning_rate:
    base: 3.0e-05
    qwen_vl_interface: 1.0e-05
    action_model: 0.0001
  lr_scheduler_type: cosine_with_min_lr
  scheduler_specific_kwargs:
    min_lr: 5.0e-07
  freeze_modules: true
  loss_scale:
    vla: 1.0
    vlm: 0.1
  repeated_diffusion_steps: 4
  max_grad_norm: 1.0
  warmup_ratio: 0.1
  weight_decay: 0.0
  logging_frequency: 10
  gradient_clipping: 1.0
  gradient_accumulation_steps: 1
  optimizer:
    name: AdamW
    betas:
    - 0.9
    - 0.95
    eps: 1.0e-08
    weight_decay: 1.0e-08
  is_resume: false
  resume_epoch: null
  resume_step: null
  enable_gradient_checkpointing: true
  enable_mixed_precision_training: true
is_resume: false
output_dir: ./results/Checkpoints/1008_qwenLfm_briage