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 | 0.0001 |
| LR Scheduler | constant_with_warmup |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 970 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9294 |
| Val Accuracy | 0.8712 |
| Test Accuracy | 0.8748 |
The model was fine-tuned on the following 50 CIFAR100 classes:
woman, mouse, skunk, train, pear, sweet_pepper, dinosaur, willow_tree, apple, house, snake, otter, streetcar, couch, porcupine, skyscraper, camel, elephant, hamster, orchid, chimpanzee, aquarium_fish, telephone, bowl, cloud, rose, ray, shark, orange, poppy, bridge, bear, boy, butterfly, bee, sea, wardrobe, bus, wolf, plain, lobster, cockroach, man, maple_tree, table, bottle, dolphin, keyboard, beaver, castle
Base model
microsoft/resnet-101