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 | cosine_with_restarts |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 624 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9430 |
| Val Accuracy | 0.8619 |
| Test Accuracy | 0.8686 |
The model was fine-tuned on the following 50 CIFAR100 classes:
flatfish, poppy, spider, girl, chimpanzee, camel, butterfly, otter, pear, ray, motorcycle, pickup_truck, tank, bed, rocket, lamp, lizard, aquarium_fish, woman, wardrobe, chair, plate, mushroom, bicycle, skunk, seal, palm_tree, streetcar, bottle, bowl, rabbit, telephone, castle, house, caterpillar, cattle, orchid, bee, maple_tree, clock, crab, skyscraper, pine_tree, oak_tree, orange, tulip, bus, rose, bear, raccoon
Base model
microsoft/resnet-101