groot-bs64 / README.md
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metadata
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 2026-05-26T22:35:50+00:00. Embodiment: UNITREE_G1_SONIC. Trained on 1 GPUs.

Hyperparameters

timestamp           = 2026-05-26T21:02:27+00:00
log_file            = /home/ubuntu/groot-files/logs/train-2026-05-26-210227.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
num_gpus            = 1
visible_gpu         = 1
global_batch_size   = 64
max_steps           = 15000
save_steps          = 3000
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.