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 | 3e-05 |
| LR Scheduler | linear |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 340 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8569 |
| Val Accuracy | 0.8176 |
| Test Accuracy | 0.8188 |
The model was fine-tuned on the following 50 CIFAR100 classes:
elephant, spider, can, porcupine, bus, couch, sunflower, maple_tree, poppy, mushroom, beetle, apple, bowl, mouse, skyscraper, shrew, squirrel, lamp, bee, bear, turtle, tiger, wardrobe, palm_tree, rabbit, crocodile, plate, caterpillar, plain, lizard, tractor, forest, leopard, bed, sea, worm, rocket, kangaroo, raccoon, aquarium_fish, beaver, possum, bridge, trout, crab, skunk, cattle, keyboard, pickup_truck, girl
Base model
microsoft/resnet-101