| 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: ./playground/Datasets/LEROBOT_LIBERO_DATA | |
| dataset_py: lerobot_datasets | |
| per_device_batch_size: 8 | |
| video_backend: torchvision_av | |
| framework: | |
| action_model: | |
| action_dim: 7 | |
| action_horizon: 8 | |
| action_model_type: DiT-B | |
| add_pos_embed: true | |
| diffusion_model_cfg: | |
| cross_attention_dim: 4096 | |
| dropout: 0.2 | |
| final_dropout: true | |
| interleave_self_attention: true | |
| norm_type: ada_norm | |
| num_layers: 16 | |
| output_dim: 1024 | |
| positional_embeddings: null | |
| future_action_window_size: 7 | |
| hidden_size: 1024 | |
| max_seq_len: 1024 | |
| noise_beta_alpha: 1.5 | |
| noise_beta_beta: 1.0 | |
| noise_s: 0.999 | |
| num_inference_timesteps: 4 | |
| num_target_vision_tokens: 32 | |
| num_timestep_buckets: 1000 | |
| past_action_window_size: 0 | |
| state_dim: 7 | |
| name: QwenGR00T | |
| qwenvl: | |
| base_vlm: /mnt/18T/starVLAproject/Qwen3-VL-8B-Instruct | |
| output_dir: /starvla/Checkpoints/libero4in1_QwenGR00T_2node_0201_1721 | |
| run_id: libero4in1_QwenGR00T_2node_0201_1721 | |
| run_root_dir: /starvla/Checkpoints | |
| seed: 42 | |
| trainer: | |
| eval_interval: 100 | |
| freeze_modules: true | |
| gradient_accumulation_steps: 4 | |
| 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: 100 | |
| lr_scheduler_type: cosine_with_min_lr | |
| max_train_steps: 80000 | |
| 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: 1.0e-06 | |
| wandb_entity: xiguapi | |
| wandb_project: Qwen3VL_libero_all_QwenGR00T_2node | |