GR00T SO101 Ball In Box

Fine-tuned GR00T policy for the yeopeter1031/so101-ball-in-box LeRobot dataset.

Training

  • Base model: nvidia/GR00T-N1.5-3B
  • Dataset: yeopeter1031/so101-ball-in-box
  • Policy type: groot
  • Steps: 2500
  • Batch size: 16
  • Effective samples: 40000
  • Image transforms: enabled
  • Final checkpoint: 002500
  • Final logged loss: 0.065

Image Transforms

This checkpoint was trained with LeRobot on-the-fly image transforms enabled:

  • Color jitter: brightness, contrast, saturation, hue
  • Sharpness jitter
  • Random affine

The augmented frames are not materialized as a separate dataset; transforms are applied by the dataloader during training.

Files

  • model.safetensors: fine-tuned policy weights
  • config.json: policy config
  • train_config.json: training config
  • policy_preprocessor.json: input preprocessing config
  • policy_postprocessor.json: output postprocessing config

Notes

This is an offline training checkpoint. Real robot or replay inference should be used to evaluate task success rate.

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