Model-J ResNet
Collection
1001 items
โข
Updated
This model is part of the Model-J dataset, introduced in:
Learning on Model Weights using Tree Experts (CVPR 2025) by Eliahu Horwitz*, Bar Cavia*, Jonathan Kahana*, Yedid Hoshen
๐ Project | ๐ Paper | ๐ป GitHub | ๐ค Dataset
| Attribute | Value |
|---|---|
| Subset | ResNet |
| Split | train |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 5e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 291 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9293 |
| Val Accuracy | 0.8688 |
| Test Accuracy | 0.8652 |
The model was fine-tuned on the following 50 CIFAR100 classes:
man, chair, lobster, leopard, spider, orchid, clock, porcupine, apple, lizard, caterpillar, sunflower, flatfish, house, sweet_pepper, tractor, television, can, bridge, bowl, lawn_mower, wardrobe, possum, crab, chimpanzee, telephone, skyscraper, poppy, beaver, tulip, skunk, seal, train, road, pickup_truck, bed, cup, shark, whale, raccoon, butterfly, castle, tank, sea, streetcar, bottle, rocket, trout, mouse, bear
Base model
microsoft/resnet-101