OpenVLA Fine-Tuned on LIBERO Spatial
This repository hosts my fine-tuned OpenVLA checkpoint trained on the modified LIBERO Spatial dataset variant libero_spatial_no_noops.
Model Summary
- Base model:
openvla-7b
- Fine-tuning method:
LoRA
- Training steps:
50,000
- Final evaluation suite:
libero_spatial
- Final score:
40/50 = 80.0%
Dataset
This model was trained on:
- Dataset name:
libero_spatial_no_noops
- Dataset format:
RLDS / TFRecord
- Dataset download:
https://huggingface.co/datasets/openvla/modified_libero_rlds/tree/main/libero_spatial_no_noops/1.0.0
Place the dataset under:
datasets/modified_libero_rlds/libero_spatial_no_noops/1.0.0
Checkpoint Contents
This Hugging Face model repository contains the final merged fine-tuned checkpoint exported from the run directory:
runs/openvla-7b+libero_spatial_no_noops+b16+lr-0.0005+lora-r32+dropout-0.0--image_aug
Upstream Project
This model is based on the upstream OpenVLA project:
https://github.com/openvla/openvla
License
- Repository code in upstream OpenVLA is released under the
MIT License
- Pretrained OpenVLA models may also be subject to the
Llama Community License
Llama license:
https://ai.meta.com/llama/license/
