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 | 3e-05 |
| LR Scheduler | cosine |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 313 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.3141 |
| Val Accuracy | 0.2944 |
| Test Accuracy | 0.3076 |
The model was fine-tuned on the following 50 CIFAR100 classes:
maple_tree, flatfish, bicycle, bus, streetcar, lion, dinosaur, plain, bottle, beaver, mountain, crocodile, cattle, aquarium_fish, crab, bowl, sea, rabbit, palm_tree, man, wardrobe, shrew, table, chimpanzee, rose, telephone, wolf, seal, house, beetle, apple, pickup_truck, bed, camel, mouse, kangaroo, lobster, tulip, leopard, ray, clock, couch, train, dolphin, willow_tree, hamster, tractor, plate, butterfly, baby
Base model
microsoft/resnet-101