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 | 9e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 601 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9922 |
| Val Accuracy | 0.9080 |
| Test Accuracy | 0.9062 |
The model was fine-tuned on the following 50 CIFAR100 classes:
forest, rocket, tiger, worm, orange, poppy, aquarium_fish, sea, elephant, willow_tree, trout, chair, woman, squirrel, snail, ray, bee, couch, flatfish, wolf, dinosaur, mouse, rabbit, streetcar, shark, porcupine, lobster, lawn_mower, man, bed, bear, pear, dolphin, sunflower, otter, cup, can, keyboard, fox, mushroom, spider, plate, bicycle, lamp, camel, cockroach, skunk, bottle, tulip, hamster
Base model
microsoft/resnet-101