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 | cosine |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 630 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9824 |
| Val Accuracy | 0.8904 |
| Test Accuracy | 0.8890 |
The model was fine-tuned on the following 50 CIFAR100 classes:
pear, mouse, pine_tree, girl, cup, skunk, snail, wardrobe, crocodile, palm_tree, willow_tree, tulip, lion, dinosaur, poppy, camel, castle, beetle, chimpanzee, telephone, couch, chair, cockroach, lawn_mower, snake, apple, whale, spider, porcupine, streetcar, television, keyboard, bee, raccoon, can, seal, worm, leopard, sunflower, shark, boy, lamp, oak_tree, sweet_pepper, rabbit, plate, house, ray, pickup_truck, clock
Base model
microsoft/resnet-101