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ACT Model for Dice Manipulation with Bounding Box Data
This model was trained on the so100_dice_red_v2 dataset with enhanced state vectors that incorporate bounding box information from PaLI-Gemma object detection.
Training Details
- Base dataset: so100_dice_red_v2
- State vectors: Modified to include subtle guidance based on dice position
- Training steps: 50,000
- Final loss: 0.046
Usage
This model can be used with the LeRobot framework for picking up dice with improved accuracy.
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