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 | 5e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 679 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9077 |
| Val Accuracy | 0.8771 |
| Test Accuracy | 0.8646 |
The model was fine-tuned on the following 50 CIFAR100 classes:
woman, beaver, aquarium_fish, boy, keyboard, lion, cattle, bicycle, motorcycle, raccoon, tulip, crab, lawn_mower, porcupine, dolphin, streetcar, telephone, chair, couch, chimpanzee, sunflower, house, tank, whale, turtle, mountain, dinosaur, cockroach, pickup_truck, flatfish, orchid, shark, ray, kangaroo, cloud, rose, palm_tree, snail, sea, butterfly, camel, sweet_pepper, cup, fox, rocket, skunk, lobster, oak_tree, rabbit, train
Base model
microsoft/resnet-101