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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 7e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 116 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8787 |
| Val Accuracy | 0.8400 |
| Test Accuracy | 0.8350 |
The model was fine-tuned on the following 50 CIFAR100 classes:
forest, bus, mountain, seal, plain, girl, man, flatfish, sea, streetcar, ray, bottle, rose, bear, beetle, worm, bridge, skyscraper, pickup_truck, lawn_mower, sunflower, trout, camel, road, skunk, boy, bed, lobster, hamster, pear, orchid, tiger, bowl, raccoon, shark, spider, plate, baby, mushroom, turtle, cattle, porcupine, chimpanzee, whale, aquarium_fish, kangaroo, dinosaur, television, table, tulip
Base model
microsoft/resnet-101