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 | 0.0005 |
| LR Scheduler | constant_with_warmup |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 228 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9196 |
| Val Accuracy | 0.8616 |
| Test Accuracy | 0.8672 |
The model was fine-tuned on the following 50 CIFAR100 classes:
cup, pear, woman, cloud, mouse, flatfish, snake, bottle, man, porcupine, dolphin, boy, can, couch, camel, leopard, skunk, bicycle, butterfly, chair, kangaroo, tank, caterpillar, fox, snail, cattle, table, aquarium_fish, pine_tree, mountain, wolf, skyscraper, ray, bus, bee, television, cockroach, road, palm_tree, bridge, forest, wardrobe, lobster, baby, spider, possum, train, chimpanzee, maple_tree, house
Base model
microsoft/resnet-101