| datasets: |
| vla_data: |
| CoT_prompt: Your task is {instruction}. To identify the key objects for your task. |
| Locate their bounding boxes in [x1,y1,x2,y2] format. |
| data_mix: libero_all |
| data_root_dir: /inspire/ssd/project/embodied-basic-model/zhangjianing-253108140206/experiment/starVLA/playground/Datasets/LEROBOT_LIBERO_DATA/libero |
| dataset_py: lerobot_datasets |
| per_device_batch_size: 8 |
| video_backend: torchvision_av |
| framework: |
| action_model: |
| action_dim: 7 |
| action_hidden_dim: 2560 |
| action_model_type: DiT-B |
| future_action_window_size: 7 |
| past_action_window_size: 0 |
| name: QwenOFT |
| qwenvl: |
| base_vlm: /inspire/qb-ilm/project/embodied-basic-model/zhangjianing-253108140206/model/cubev0-200000-Qwen3-VL |
| output_dir: ./results/Checkpoints/125_cube_oft_gr00t |
| run_id: 125_cube_oft_gr00t |
| run_root_dir: ./results/Checkpoints |
| seed: 42 |
| trainer: |
| eval_interval: 1000 |
| freeze_modules: true |
| gradient_accumulation_steps: 1 |
| gradient_clipping: 1.0 |
| is_resume: false |
| learning_rate: |
| action_model: 0.0001 |
| base: 2.5e-05 |
| qwen_vl_interface: 1.0e-05 |
| logging_frequency: 10 |
| lr_scheduler_type: cosine_with_min_lr |
| max_train_steps: 30000 |
| num_warmup_steps: 100 |
| optimizer: |
| betas: |
| - 0.9 |
| - 0.95 |
| eps: 1.0e-08 |
| weight_decay: 1.0e-08 |
| save_interval: 5000 |
| scheduler_specific_kwargs: |
| min_lr: 1.0e-06 |
| wandb_entity: 1732949190-tongji-university |
| wandb_project: wallx4libero |
|
|
