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_with_warmup |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 384 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9668 |
| Val Accuracy | 0.8832 |
| Test Accuracy | 0.8800 |
The model was fine-tuned on the following 50 CIFAR100 classes:
table, bee, bear, wolf, cup, tiger, oak_tree, rabbit, snail, otter, hamster, kangaroo, mountain, tractor, man, plain, bottle, skyscraper, wardrobe, pear, boy, shrew, maple_tree, orange, camel, bus, train, bicycle, chimpanzee, lamp, lobster, plate, streetcar, apple, woman, butterfly, clock, leopard, caterpillar, cockroach, bed, girl, ray, shark, whale, lawn_mower, mouse, rose, flatfish, dolphin
Base model
microsoft/resnet-101