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 | 7e-05 |
| LR Scheduler | constant |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 890 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8822 |
| Val Accuracy | 0.8480 |
| Test Accuracy | 0.8444 |
The model was fine-tuned on the following 50 CIFAR100 classes:
train, fox, caterpillar, sweet_pepper, boy, worm, baby, porcupine, possum, aquarium_fish, chair, bottle, rose, beaver, cup, seal, camel, couch, skunk, leopard, flatfish, clock, trout, pickup_truck, lawn_mower, wolf, butterfly, snake, bridge, mouse, dinosaur, bus, mountain, sunflower, road, snail, cloud, willow_tree, rabbit, elephant, keyboard, crocodile, pear, chimpanzee, bed, oak_tree, hamster, shrew, tractor, turtle
Base model
microsoft/resnet-101