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 | 0.0005 |
| LR Scheduler | constant_with_warmup |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 19 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9696 |
| Val Accuracy | 0.8773 |
| Test Accuracy | 0.8736 |
The model was fine-tuned on the following 50 CIFAR100 classes:
cloud, cup, dinosaur, skunk, bottle, road, pear, bridge, leopard, possum, woman, shark, plain, mushroom, pickup_truck, turtle, dolphin, bowl, tractor, apple, wardrobe, mouse, flatfish, shrew, man, bicycle, orchid, girl, otter, trout, streetcar, spider, snake, rose, tiger, porcupine, poppy, pine_tree, ray, aquarium_fish, snail, lion, sweet_pepper, whale, camel, wolf, crab, lamp, caterpillar, beetle
Base model
microsoft/resnet-101