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 | 3e-05 |
| LR Scheduler | constant |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 305 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9091 |
| Val Accuracy | 0.8571 |
| Test Accuracy | 0.8576 |
The model was fine-tuned on the following 50 CIFAR100 classes:
apple, skunk, keyboard, hamster, lizard, rabbit, beetle, worm, turtle, maple_tree, lamp, clock, spider, ray, snake, plate, seal, motorcycle, porcupine, cup, table, rocket, boy, road, wolf, plain, beaver, aquarium_fish, sweet_pepper, television, baby, cockroach, pine_tree, possum, bridge, couch, wardrobe, tulip, snail, tractor, palm_tree, sea, leopard, rose, willow_tree, house, bicycle, sunflower, lobster, dinosaur
Base model
microsoft/resnet-101