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 | 5e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 271 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9236 |
| Val Accuracy | 0.8637 |
| Test Accuracy | 0.8616 |
The model was fine-tuned on the following 50 CIFAR100 classes:
bowl, bicycle, otter, keyboard, telephone, palm_tree, snake, pear, dolphin, sea, beaver, butterfly, oak_tree, chimpanzee, spider, porcupine, apple, sweet_pepper, snail, squirrel, man, rabbit, sunflower, shark, whale, turtle, boy, aquarium_fish, cattle, streetcar, road, willow_tree, bridge, tractor, train, lion, orange, bed, skyscraper, cockroach, worm, fox, elephant, wardrobe, tank, chair, woman, maple_tree, lobster, beetle
Base model
microsoft/resnet-101