# facebookresearch/simsiam

PyTorch implementation of SimSiam https//arxiv.org/abs/2011.10566

Repository: https://github.com/facebookresearch/simsiam
Canonical: https://ross.abutalabs.com/products/simsiam
Language: Python
License: NOASSERTION
License Family: other
Archived: true
Last push: 2023-01-26T11:34:46+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1983, "days_push": 1315, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, archived, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1237, forks 174 (observed 2026-08-28T04:04:05.318453+00:00)

## What it is
A PyTorch implementation of SimSiam, a simple Siamese-based self-supervised representation learning method from Facebook AI Research (CVPR 2021). It provides training scripts for unsupervised pre-training of ResNet-50 on ImageNet and linear classification evaluation, with pre-trained checkpoints.

## Use cases
- train a self-supervised image representation model on ImageNet
- reproduce SimSiam paper results
- pre-train a ResNet-50 backbone without labels
- evaluate learned features with linear classification
- compare self-supervised learning methods like MoCo and SimSiam

## When to choose
- you need a reference implementation of SimSiam for research or reproduction
- you want to pre-train vision backbones without labels on multi-GPU hardware
- you need released pre-trained checkpoints for transfer learning experiments

## When to avoid
- you need single-GPU or DataParallel training - only DistributedDataParallel is supported
- you want a maintained library with new features - the repo is a research code release
- you need a plug-and-play self-supervised framework rather than paper-specific scripts

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning
- domain: machine-learning, computer-vision, deep-learning
- platform: python
- tags: self-supervised-learning, representation-learning, contrastive-learning, pytorch, research-code, imagenet, resnet, gpu, linux

## Member repositories
- facebookresearch/simsiam (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:05.318453+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T08:21:52.168411+00:00, confidence not recorded.
  - readme: https://github.com/facebookresearch/simsiam (fetched 2026-08-28T04:04:05.318453+00:00, sha eeb6213067a1)
- Data as of 2026-08-30T08:39:29.467469+00:00.