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rn50_supcon_bs4096_e1000
erow/rn50_supcon_bs4096_e1000
rn50_supcon_bs4096_e1000 is a machine learning model from erow. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for pytorch. The card lists the license as apache-2.0.
ResNet-50 supervised contrastive run on ImageNet-1K with FastSSL (mainpretrain.py). Implemented as SimLAP with identical pairs and an open gate (SimLAP.type="identical", SimLAP.gatefn=@OpenGate).
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Updated Sep 19, 2026
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.pth4.1 GB · 100%
At a glance
- Library
- pytorch
- License
- apache-2.0
- Access
- Public
- Created
- Sep 19, 2026
- Updated
- Sep 19, 2026
- SHA
- 0981fcee
Model card
From the Hugging Face model README
rn50_supcon_bs4096_e1000
ResNet-50 supervised contrastive run on ImageNet-1K with FastSSL (main_pretrain.py). Implemented as SimLAP with identical pairs and an open gate (SimLAP.type="identical", SimLAP.gate_fn=@OpenGate).
| Method | SupCon via SimLAP identical + OpenGate |
| Backbone | ResNet-50, projector 2048-2048-256, τ=0.1, 1000 classes |
| Data | ImageNet-1K, 224², two global crops |
| Optim | LARS, lr=0.2, wd=1e-4, warmup 40, 1000 epochs planned |
| Batch | 4×1024 = 4096 |
| Latest | checkpoint.pth (epoch 840 / 1000) |
Periodic snapshots every 50 epochs: checkpoint-0.pth … checkpoint-800.pth. Training configs are config.yml and config.gin.
- Library
- pytorch
- License
- apache-2.0
- Created
- Sep 19, 2026
- Updated
- Sep 19, 2026