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 |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 58 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9896 |
| Val Accuracy | 0.9045 |
| Test Accuracy | 0.8970 |
The model was fine-tuned on the following 50 CIFAR100 classes:
mushroom, raccoon, castle, aquarium_fish, butterfly, spider, hamster, beetle, beaver, tank, bridge, fox, kangaroo, telephone, whale, worm, cockroach, forest, wolf, shrew, flatfish, road, sea, house, orange, bear, girl, camel, willow_tree, train, caterpillar, motorcycle, bus, sweet_pepper, leopard, man, dolphin, rocket, otter, tractor, crocodile, pickup_truck, lizard, trout, plain, couch, wardrobe, ray, television, apple
Base model
microsoft/resnet-101