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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 0.0003 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 585 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9850 |
| Val Accuracy | 0.9128 |
| Test Accuracy | 0.9070 |
The model was fine-tuned on the following 50 CIFAR100 classes:
elephant, whale, baby, raccoon, motorcycle, tulip, poppy, tractor, road, apple, bridge, cattle, camel, orchid, lion, kangaroo, beetle, boy, rabbit, ray, lobster, pear, telephone, aquarium_fish, spider, worm, rocket, cockroach, trout, mountain, butterfly, cup, leopard, rose, tank, clock, porcupine, dolphin, crocodile, chimpanzee, oak_tree, streetcar, beaver, maple_tree, bowl, dinosaur, bus, chair, couch, wardrobe
Base model
microsoft/resnet-101