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 | linear |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 530 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9411 |
| Val Accuracy | 0.8779 |
| Test Accuracy | 0.8740 |
The model was fine-tuned on the following 50 CIFAR100 classes:
lion, rabbit, bear, skunk, rocket, train, lamp, tulip, television, lizard, wardrobe, sea, man, rose, boy, sweet_pepper, bee, keyboard, bottle, plain, worm, butterfly, pine_tree, oak_tree, cloud, chair, tiger, mushroom, possum, house, lobster, squirrel, shrew, bus, girl, fox, table, trout, cockroach, lawn_mower, hamster, poppy, tank, beetle, streetcar, bridge, clock, motorcycle, crocodile, pear
Base model
microsoft/resnet-101