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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 — 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.