---
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)