---
library_name: lerobot
pipeline_tag: robotics
tags: [act, lerobot, robotics, dg5f, ur5e, gelsight]
---

# ACT — v6 blue89 180ep, GelSight 500x375 (native)

- **Dataset**: [Kaz55/dg5f_ur5e_v6_blue89_180ep](https://huggingface.co/datasets/Kaz55/dg5f_ur5e_v6_blue89_180ep) — 180 episodes / 208,109 frames
- **GelSight**: 500x375 (native)
- **RealSense**: 640x480
- **Policy**: ACT, chunk_size=60, n_action_steps=60
- **Training**: 100,000 steps (~3.84 epochs), batch 8, seed 1000

## Inputs

`observation.state` (26) + RealSense x2 + GelSight x2

`observation.velocity` and `observation.effort` exist in the dataset but are
**deliberately excluded** — feature auto-derivation would otherwise feed them to
the policy and add a second difference between runs.

## Caveat

This is a different dataset from the `blue_180ep` sweep (186 ep / 186,152 frames),
so losses are not directly comparable across the two. On the related `combined`
sweep, training loss was identical at every GelSight resolution **including
no-GelSight-at-all**, so treat loss as a sanity check rather than evidence about
tactile resolution; that needs on-robot evaluation.