| datasets: | |
| vla_data: | |
| data_mix: robochallenge_table30v2_shred_paper | |
| data_root_dir: /home/Travor/starvla-assets/Datasets/RoboChallenge_table30v2 | |
| dataset_py: lerobot_datasets | |
| delete_pause_frame: false | |
| num_workers: 2 | |
| per_device_batch_size: 1 | |
| persistent_workers: true | |
| pin_memory: true | |
| prefetch_factor: 4 | |
| sequential_step_sampling: false | |
| video_backend: decord | |
| framework: | |
| action_model: | |
| action_dim: 8 | |
| action_hidden_dim: 1024 | |
| action_horizon: 8 | |
| action_model_type: MLP | |
| name: QwenOFT | |
| qwenvl: | |
| attn_implementation: sdpa | |
| base_vlm: /home/Travor/starvla-assets/Pretrained_models/Qwen3.5-0.8B | |
| output_dir: /tmp/starvla-full-validation-results/dataloader-throughput-fulltrain-100step-workers | |
| run_id: dataloader-throughput-fulltrain-100step-workers | |
| run_root_dir: /tmp/starvla-full-validation-results | |
| seed: 42 | |
| trainer: | |
| eval_interval: 100000 | |
| freeze_modules: qwen_vl_interface.model | |
| gradient_clipping: 1.0 | |
| learning_rate: | |
| action_model: 0.0001 | |
| base: 2.5e-05 | |
| qwen_vl_interface: 1.0e-05 | |
| logging_frequency: 5 | |
| lr_scheduler_type: cosine_with_min_lr | |
| max_train_steps: 100 | |
| num_warmup_steps: 10 | |
| optimizer: | |
| betas: | |
| - 0.9 | |
| - 0.95 | |
| eps: 1.0e-08 | |
| weight_decay: 1.0e-08 | |
| save_interval: 100 | |
| scheduler_specific_kwargs: | |
| min_lr: 1.0e-06 | |
| wandb_entity: your_wandb_entity | |
| wandb_project: starVLA_local_full_validation | |