Qwen3vl4b-OFT-RoboDojo / config.yaml
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datasets:
vla_data:
action_mode: abs
data_mix: robodojo_v21_all_h50_q99
data_root_dir: ./playground/Datasets
dataset_py: lerobot_datasets
obs_image_size:
- 224
- 224
per_device_batch_size: 16
video_backend: torchvision_av
framework:
action_model:
action_dim: 14
action_hidden_dim: 2560
action_horizon: 50
action_model_type: MLP
name: QwenOFT
qwenvl:
attn_implementation: flash_attention_2
base_vlm: Qwen/Qwen3-VL-4B-Instruct
output_dir: ./playground/Checkpoints/robodojo_v21_all_h50_q99_qwenoft
run_id: robodojo_v21_all_h50_q99_qwenoft
run_root_dir: ./playground/Checkpoints
seed: 42
trainer:
eval_interval: 100
freeze_modules: ''
gradient_clipping: 1.0
is_resume: true
learning_rate:
action_model: 0.0001
base: 1.0e-05
qwen_vl_interface: 1.0e-05
logging_frequency: 10
lr_scheduler_type: cosine_with_min_lr
max_train_steps: 150000
num_warmup_steps: 5000
optimizer:
betas:
- 0.9
- 0.95
eps: 1.0e-08
weight_decay: 1.0e-08
save_interval: 10000
scheduler_specific_kwargs:
min_lr: 5.0e-07
wandb_entity: your_wandb_entity
wandb_project: llavavla