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 | cosine |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 622 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9980 |
| Val Accuracy | 0.9019 |
| Test Accuracy | 0.9028 |
The model was fine-tuned on the following 50 CIFAR100 classes:
wolf, rocket, hamster, dinosaur, butterfly, crocodile, mushroom, cup, spider, elephant, orchid, skunk, girl, porcupine, television, raccoon, house, cloud, crab, cattle, train, fox, bus, rabbit, palm_tree, pickup_truck, shark, willow_tree, bottle, flatfish, boy, lamp, man, plain, clock, castle, poppy, tiger, worm, chimpanzee, lawn_mower, bridge, otter, squirrel, beaver, caterpillar, rose, can, sea, telephone
Base model
microsoft/resnet-101