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0xemkey/rlt_lift_finetuned_pi05
rlt_lift_finetuned_pi05 is a reinforcement learning model from 0xemkey. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product. It is set up for pytorch. The card lists the license as other.
Private backup of the RLT fine-tuning artifacts for the MIML-VLA Lift task.
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Updated May 29, 2026
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From the Hugging Face model README
Private backup of the RLT fine-tuning artifacts for the MIML-VLA Lift task.
This RLT checkpoint was initialized from the behavior-cloning fine-tuned Pi0.5 Lift model:
0xemkey/finetuned_with_lift_pi05/data/ubuntu/checkpoints/finetuned_with_lift_pi05/step_000100This repository does not store the full 16GB Pi0.5 base model again. It stores the RLT adapter/checkpoint artifacts, logs, plots, and run metadata.
20260529_204704train_rlt_online_miml_lift.py/data/ubuntu/checkpoints/finetuned_with_lift_pi05/step_000100The RLT infrastructure worked: rollout, updates, checkpoints, CSV logs, and plots were produced.
However, task success was not achieved. The main blocker was gripper command mapping/override:
+1.0, interpreted as open.Expected convention:
denorm_gripper < 0 -> env_gripper = -1.0 closed
denorm_gripper > 0 -> env_gripper = +1.0 open
rlt_final_debug.ptrlt_episode_0005.pt if availableonline_rl_step_metrics.csvonline_rl_episode_metrics.csvonline_rl_update_metrics.csvplot_summary.txtonline_rl_dashboard.pngonline_rl_reward_curve.pngonline_rl_distance_height_curve.pngonline_rl_residual_curve.pngonline_rl_alignment_curve.pngonline_rl_loss_curve.pngBefore running longer RLT training, fix gripper mapping so negative gripper commands are sent to the environment as closed:
-1.0 = closed
+1.0 = open