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nvidia/GR00T-N1.7-3B on 2026-05-28T10:23:24+00:00.
Embodiment: UNITREE_G1_SONIC. Trained on 1 GPUs.timestamp = 2026-05-28T09:23:35+00:00
log_file = /home/ubuntu/groot-files/logs/train-2026-05-28-092335.log
base_model = nvidia/GR00T-N1.7-3B
embodiment_tag = UNITREE_G1_SONIC
dataset_dir = /home/ubuntu/groot-files/dataset_wbc_train
eval_dataset_dir = /home/ubuntu/groot-files/dataset_wbc_eval
eval_steps = 500
eval_num_batches = 50
checkpoint_dir = /home/ubuntu/groot-files/checkpoints/run-2026-05-28-092335
num_gpus = 1
global_batch_size = 16
max_steps = 10000
save_steps = 1000
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-wbc
wandb_run_name = groot-wbc-16checkpoint-N/) are pushed incrementally during
training; the top-level files in this repo are the final model state.