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 | 7e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 516 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9771 |
| Val Accuracy | 0.8944 |
| Test Accuracy | 0.8732 |
The model was fine-tuned on the following 50 CIFAR100 classes:
poppy, porcupine, orange, cattle, bowl, house, couch, girl, aquarium_fish, rocket, forest, boy, lawn_mower, woman, whale, plain, cockroach, bottle, cup, castle, snake, tank, bee, lobster, mushroom, pickup_truck, bed, lizard, telephone, sea, pine_tree, kangaroo, possum, palm_tree, bridge, raccoon, dolphin, skyscraper, shrew, leopard, ray, plate, tiger, beaver, sunflower, can, beetle, chimpanzee, bus, flatfish
Base model
microsoft/resnet-101