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 | 0.0003 |
| LR Scheduler | constant_with_warmup |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 150 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9944 |
| Val Accuracy | 0.8920 |
| Test Accuracy | 0.8976 |
The model was fine-tuned on the following 50 CIFAR100 classes:
tank, elephant, woman, can, chimpanzee, train, beaver, mushroom, pear, bowl, road, poppy, raccoon, aquarium_fish, leopard, baby, seal, oak_tree, bridge, dolphin, bear, lawn_mower, castle, camel, orchid, house, keyboard, cattle, telephone, otter, sunflower, bee, lion, bus, wardrobe, boy, shrew, hamster, clock, palm_tree, sea, butterfly, pickup_truck, spider, bottle, porcupine, skyscraper, lizard, cloud, crab
Base model
microsoft/resnet-101