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 | 0.0001 |
| LR Scheduler | constant |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 790 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9632 |
| Val Accuracy | 0.8771 |
| Test Accuracy | 0.8746 |
The model was fine-tuned on the following 50 CIFAR100 classes:
can, otter, squirrel, flatfish, shrew, poppy, whale, plate, bottle, wardrobe, skyscraper, house, lawn_mower, girl, mouse, lizard, butterfly, castle, pickup_truck, palm_tree, skunk, spider, forest, rabbit, rose, bicycle, bear, leopard, couch, bee, tractor, elephant, lamp, aquarium_fish, worm, sunflower, cup, dinosaur, orchid, possum, dolphin, kangaroo, caterpillar, crab, cockroach, rocket, cattle, baby, table, maple_tree
Base model
microsoft/resnet-101