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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 501 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9068 |
| Val Accuracy | 0.8517 |
| Test Accuracy | 0.8582 |
The model was fine-tuned on the following 50 CIFAR100 classes:
possum, baby, bottle, rabbit, bowl, keyboard, spider, cockroach, oak_tree, shark, dolphin, girl, sea, table, leopard, bee, aquarium_fish, wolf, plate, bed, willow_tree, lobster, bicycle, beaver, skunk, ray, trout, lizard, wardrobe, pear, motorcycle, bear, cattle, train, orchid, dinosaur, mountain, chimpanzee, telephone, raccoon, crab, porcupine, poppy, hamster, woman, forest, streetcar, whale, caterpillar, lawn_mower
Base model
microsoft/resnet-101