feat(pi0): add train_expert_only and freeze_vision_encoder flags to pi0 and pi0.5 (#2727)

* feat(pi0): add train_expert_only and freeze_vision_encoder options

* pi_05: train_expert_only and freeze_vision_encoder flags

* comment clean up

* docs: add finetuning parameters to pi0 and pi05 docs

* updating docs to follow standards
This commit is contained in:
arya
2025-12-31 06:54:28 -08:00
committed by GitHub
parent 6d0d65a5fe
commit 9701b9c273
6 changed files with 78 additions and 0 deletions
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@@ -64,6 +64,8 @@ python src/lerobot/scripts/lerobot_train.py \
--policy.compile_model=true \
--policy.gradient_checkpointing=true \
--policy.dtype=bfloat16 \
--policy.freeze_vision_encoder=false \
--policy.train_expert_only=false \
--steps=3000 \
--policy.device=cuda \
--batch_size=32
@@ -79,6 +81,15 @@ python src/lerobot/scripts/lerobot_train.py \
- [lerobot/pi0_base](https://huggingface.co/lerobot/pi0_base)
- [lerobot/pi0_libero](https://huggingface.co/lerobot/pi0_libero) (specifically trained on the Libero dataset)
### Training Parameters Explained
| Parameter | Default | Description |
| ----------------------- | ------- | ------------------------------------------- |
| `freeze_vision_encoder` | `false` | Do not freeze the vision encoder |
| `train_expert_only` | `false` | Do not freeze the VLM, train all parameters |
**💡 Tip**: Setting `train_expert_only=true` freezes the VLM and trains only the action expert and projections, allowing finetuning with reduced memory usage.
## License
This model follows the **Apache 2.0 License**, consistent with the original [OpenPI repository](https://github.com/Physical-Intelligence/openpi).