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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | linear |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 458 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9809 |
| Val Accuracy | 0.9013 |
| Test Accuracy | 0.9000 |
The model was fine-tuned on the following 50 CIFAR100 classes:
cloud, tractor, crocodile, couch, camel, kangaroo, woman, lobster, spider, plain, cockroach, streetcar, table, lawn_mower, mushroom, forest, can, poppy, bus, keyboard, bottle, dinosaur, otter, pine_tree, possum, cattle, elephant, wardrobe, rocket, caterpillar, chair, snake, clock, hamster, cup, beaver, shark, raccoon, tank, pickup_truck, tiger, chimpanzee, bear, crab, willow_tree, whale, palm_tree, squirrel, apple, pear
Base model
microsoft/resnet-101