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2.59 kB
| 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: galbot_sweep_rubbish_all_data | |
| data_root_dir: /mnt/project | |
| dataset_py: lerobot_datasets | |
| delete_pause_frame: false | |
| image_size: | |
| - 224 | |
| - 224 | |
| per_device_batch_size: 48 | |
| training_task_weights: | |
| - 1 | |
| - 1 | |
| - 1 | |
| - 1 | |
| use_delta_action: false | |
| framework: | |
| action_model: | |
| action_dim: 138 | |
| action_horizon: 16 | |
| action_model_type: DiT-L | |
| add_pos_embed: true | |
| diffusion_model_cfg: | |
| cross_attention_dim: 2560 | |
| dropout: 0.2 | |
| final_dropout: true | |
| interleave_self_attention: true | |
| norm_type: ada_norm | |
| num_layers: 16 | |
| output_dim: 2560 | |
| positional_embeddings: null | |
| future_action_window_size: 15 | |
| future_obs_index: 16 | |
| hidden_size: 2560 | |
| max_num_embodiments: 32 | |
| 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 | |
| num_views: 1 | |
| obs_horizon: 2 | |
| obs_loss_weight: 1.0 | |
| only_policy: true | |
| only_wo_video_gen: false | |
| past_action_window_size: 0 | |
| policy_and_video_gen: false | |
| state_dim: 16 | |
| vision_encoder_path: /mnt/home/liukai/World-Action-Model/pretrained | |
| vision_encoder_size: s | |
| vision_encoder_type: dinov3 | |
| name: QwenMMDiT | |
| qwenvl: | |
| base_vlm: /mnt/home/liukai/starVLA/playground/pretrained/vlm/Qwen3-VL-4B-Instruct | |
| output_dir: /mnt/project/world_model/checkpoints/lda/post-train/galbot/gripper/galbot_sweep_rubbish_all_data | |
| run_id: galbot_sweep_rubbish_all_data | |
| run_root_dir: /mnt/project/world_model/checkpoints/lda/post-train/galbot/gripper | |
| seed: 42 | |
| trainer: | |
| eval_interval: 1000 | |
| freeze_modules: qwen_vl_interface,action_model.vision_encoder | |
| gradient_accumulation_steps: 1 | |
| gradient_clipping: 1.0 | |
| is_resume: false | |
| learning_rate: | |
| action_model: 0.0001 | |
| base: 4.0e-05 | |
| qwen_vl_interface: 1.0e-05 | |
| logging_frequency: 50 | |
| lr_scheduler_type: cosine_with_min_lr | |
| max_train_steps: 100000 | |
| num_warmup_steps: 5000 | |
| optimizer: | |
| betas: | |
| - 0.9 | |
| - 0.95 | |
| eps: 1.0e-08 | |
| weight_decay: 1.0e-08 | |
| post_train: true | |
| pretrained_checkpoint: /mnt/project/world_model/checkpoints/lda/pretrain_48_node_batch_sampler_w_simvla_data/final_model/pytorch_model.pt | |
| repeated_diffusion_steps: 1 | |
| save_interval: 5000 | |
| scheduler_specific_kwargs: | |
| min_lr: 5.0e-07 | |
| wandb_entity: KaiLiu-Personal | |
| wandb_project: lda-unitree-post-train | |