| --- |
| license: mit |
| task_categories: |
| - robotics |
| tags: |
| - lerobot |
| - so-101 |
| - imitation-learning |
| - behavior-cloning |
| - hg-dagger |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # so101_eval1 |
| |
| Training dataset for **Eval 1** of the LeMonkey project (ETH Robot Learning course, FS26): |
| a SmolVLA policy that picks up a banana and places it in the bowl named by the prompt. |
| |
| - **153 teleop episodes**, **44,604 frames**, **13 task strings**. |
| - Source robot: **SO-101** (6-DOF arm), wrist-mounted USB camera at 480x640 at 30 fps. |
| - Format: [LeRobot v3](https://huggingface.co/docs/lerobot/lerobot-dataset-v3) (`codebase_version: v3.0`). |
| - Aggregated from 6 per-color recording sessions: |
| - 118 behavior-cloning demos (blue / red / green, ~39 each) |
| - 35 HG-DAgger correction demos (blue / red / green) recorded against the behavior-cloning policy's failure positions |
| - The DAgger sources were normalized to the BC schema (rename `camera1`->`front`, drop `is_intervention`) before aggregation. |
|
|
| ## Trained policy |
|
|
| The deployed Eval 1 policy is [`HBOrtiz/so101_smolvla_eval1`](https://huggingface.co/HBOrtiz/so101_smolvla_eval1): |
| SmolVLA-450M, 25k steps from `lerobot/smolvla_base`, image augmentation on. |
|
|
| ## Prompt templates |
|
|
| ``` |
| Put the banana in the blue colored bowl. |
| Put the banana in the red colored bowl. |
| Put the banana in the green colored bowl. |
| (+ paraphrases and DAgger correction prompts) |
| ``` |
|
|
| ## Repository |
|
|
| Project page and code: [github.com/Ace3Z/LeMonkey](https://github.com/Ace3Z/LeMonkey) |
|
|
