Fine-tuning smolVLA on LIBERO

This project fine-tunes lerobot/smolvla_base using the HuggingFaceVLA/libero dataset to improve vision-language-action understanding for multi-task robotic manipulation.

Overview

  • Model: smolVLA
  • Dataset: LIBERO
  • Training: Supervised fine-tuning (SFT)
  • Task: Vision-Language-Action learning from demonstrations

Dataset

LIBERO provides multi-task robotic manipulation demonstrations with visual observations, language instructions, and action sequences.

Training

The model was fine-tuned on the LIBERO dataset following the original smolVLA instructions, mapping visual observations and language instructions to robot actions.

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