| license: other | |
| tags: | |
| - robotics | |
| - gr00t | |
| - isaac | |
| - humanoid | |
| base_model: nvidia/GR00T-N1.7-3B | |
| # GR00T fine-tune | |
| Fine-tuned from `nvidia/GR00T-N1.7-3B` on 2026-05-27T10:45:19+00:00. | |
| Embodiment: `UNITREE_G1_SONIC`. Trained on 4 GPUs. | |
| ## Hyperparameters | |
| ``` | |
| timestamp = 2026-05-27T10:29:39+00:00 | |
| log_file = /home/ubuntu/groot-files/logs/train-2026-05-27-102939.log | |
| base_model = nvidia/GR00T-N1.7-3B | |
| embodiment_tag = UNITREE_G1_SONIC | |
| dataset_dir = /home/ubuntu/groot-files/dataset | |
| hf_dataset = LucaFrat/dataset_100 | |
| checkpoint_dir = /home/ubuntu/groot-files/checkpoints/g1_finetune-20260527-102938 | |
| num_gpus = 4 | |
| visible_gpu = <all> | |
| global_batch_size = 16 | |
| max_steps = 4000 | |
| save_steps = 500 | |
| save_total_limit = 10 | |
| learning_rate = 1e-4 | |
| warmup_ratio = 0.05 | |
| weight_decay = 1e-5 | |
| dataloader_workers = 6 | |
| resume = <none> | |
| use_wandb = 1 | |
| wandb_project = groot-finetune | |
| wandb_run_name = <auto> | |
| ``` | |
| ## Checkpoints | |
| Intermediate checkpoints (`checkpoint-N/`) are pushed incrementally during | |
| training; the top-level files in this repo are the final model state. | |