the adapter trained on the v2 collection

README.md

@@ -0,0 +1,26 @@
+---
+license: apache-2.0
+base_model: lerobot/pi05_base
+pipeline_tag: robotics
+tags:
+- LeRobot
+- so101
+- pi0.5
+- lora
+---
+
+# pi05_so101_block_stack_sim
+
+pi0.5 fine-tuned to stack one 30 mm block on another with an [SO-101](https://github.com/TheRobotStudio/SO-ARM100), in simulation. Trained by `train/pi05_so101_lora_backbone.yaml` in [vla-test](https://github.com/danwahl/vla-test) on revision `v2` of [drwahl/so101_block_stack_sim](https://huggingface.co/drwahl/so101_block_stack_sim/tree/v2).
+
+LoRA on `lerobot/pi05_base`'s gemma_2b language backbone, with the action expert and the projection heads dense and SigLIP frozen. `adapter/` holds the adapter and the normalization processors; `train/merge.py` folds it into the base weights for a checkpoint that loads without one.
+
+```bash
+hf download drwahl/pi05_so101_block_stack_sim --local-dir pi05_so101_block_stack_sim
+uv run python train/merge.py pi05_so101_block_stack_sim/adapter pi05_so101_block_stack_sim/merged
+uv run python sim/scripts/eval.py pi05_so101_block_stack_sim/merged
+```
+
+The eval rolls the checkpoint out on the 150 held-out layouts and scores it by the gates that screened the oracle. Chunks are stitched with [Real-Time Chunking](https://www.physicalintelligence.company/research/real_time_chunking) and read back off a shape-preserving cubic before they are executed.
+
+[drwahl/pi05_so101_block_stack](https://huggingface.co/drwahl/pi05_so101_block_stack) is the same recipe trained on sim and hardware episodes together, and is the one that runs on the arm.

adapter/README.md

@@ -1,204 +0,0 @@
----
-library_name: peft
-tags:
-- base_model:adapter:lerobot/pi05_base
-- lora
----
-
-# Model Card for Model ID
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-<!-- Provide a quick summary of what the model is/does. -->
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-## Model Details
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-### Model Description
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-## Uses
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-#### Training Hyperparameters
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-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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-### Framework versions
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-- PEFT 0.20.0

adapter/adapter_model.safetensors

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adapter/train_config.json

@@ -1,7 +1,7 @@
 {
     "dataset": {
         "repo_id": "vla-test/so101_block_stack_sim",
-        "root": "/data/datasets/so101_block_stack_sim",
+        "root": "/data/datasets/so101_block_stack_sim_v2",
         "episodes": null,
         "image_transforms": {
             "enable": false,
@@ -192,8 +192,8 @@
         "scheduler_decay_lr": 2.5e-06
     },
     "reward_model": null,
-    "output_dir": "/data/checkpoints/pi05_so101_block_stack_sim",
-    "job_name": "pi05_so101_block_stack_sim",
+    "output_dir": "/data/checkpoints/pi05_so101_block_stack_sim_v2",
+    "job_name": "pi05_so101_block_stack_sim_v2",
     "resume": false,
     "seed": 1000,
     "cudnn_deterministic": false,
@@ -242,7 +242,7 @@
         "project": "vla-test",
         "entity": null,
         "notes": null,
-        "run_id": "pi05_so101_block_stack_sim",
+        "run_id": "bwqsdzte",
         "mode": null,
         "add_tags": true
     },

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openpi/vla-test/so101_block_stack_sim/norm_stats.json

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