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google-research/uda

Unsupervised Data Augmentation (UDA) observed · 2026-08-28

github.com/google-research/uda · homepage · Python · Apache-2.0 (permissive) · archived observed · 2026-08-28

Health v2 · maintenance only

10/100

  • Activity 0
  • Release rhythm 35
  • Longevity 100

Flags: no_releases archived

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 2633
  • days_rel: n/a
  • days_push: 1831
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

2205 stars · 313 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Google Research's reference implementation of Unsupervised Data Augmentation (UDA), a semi-supervised learning method that uses advanced data augmentation like back-translation and RandAugment with consistency training. It includes code for BERT-based text classification, CIFAR-10/SVHN image classification, and back-translation augmentation, runnable on GPU and Cloud TPU.

Use cases

  • train text classifiers with very few labeled examples
  • semi-supervised image classification on CIFAR-10 or SVHN
  • reproduce UDA paper results
  • back-translate text data for augmentation
  • improve ImageNet accuracy with limited labels

When to choose

  • you have scarce labeled data and abundant unlabeled data
  • you want to reproduce or build on the UDA research
  • you need a proven semi-supervised baseline for NLP or vision

When to avoid

  • you need modern maintained tooling - it targets Python 2.7 and TensorFlow 1.13
  • you want a production-ready training framework
  • you lack GPU/TPU resources or large disk space for augmented data

Facets

library · maturity maintenance

machine-learning deep-learning nlp image-processing machine-learning computer-vision python semi-supervised-learning data-augmentation tensorflow bert back-translation research-code natural-language-processing research gpu linux

6 sources

Member repositories

RepositoryRoleHealth v2
google-research/udamain10

For agents

markdown · JSON · MCP: product_card(name="google-research/uda")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem