SmolVLA Fine-tuned on LIBERO-Object
This model is a fine-tuned version of lerobot/smolvla_libero specifically trained on the LIBERO-Object task suite. It is designed to perform robotic manipulation tasks by taking visual observations and language instructions as input to predict 7-DoF actions.
🤖 Model Details
- Model Type: Vision-Language-Action (VLA)
- Base Model: lerobot/smolvla_libero (which is based on SmolVLM2)
- Task Suite: LIBERO-Object
- Framework: LeRobot
- Action Space: 7-DoF (dx, dy, dz, droll, dpitch, dyaw, gripper)
- Language: English (Task Instructions)
📊 Training Information
The model was trained by freezing the vision and language encoders and fine-tuning only the action expert modules and state projection layers.
- Dataset:
lerobot/libero(filtered for LIBERO-Object tasks) - Training Steps: 10,000 steps
- Batch Size: 8 (per device)
- Learning Rate: 1e-4 (Cosine decay with warmup)
- Hardware: Single NVIDIA T4 GPU
- Training Time: ~4 hours 50 minutes
🚀 How to Use
You can load and use this model directly with the Hugging Face lerobot library.
Installation
pip install lerobot
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