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 | 3e-05 |
| LR Scheduler | linear |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 843 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.5828 |
| Val Accuracy | 0.5811 |
| Test Accuracy | 0.5630 |
The model was fine-tuned on the following 50 CIFAR100 classes:
turtle, lawn_mower, plate, bottle, crocodile, bed, dinosaur, aquarium_fish, ray, wardrobe, rose, lobster, chair, elephant, bus, girl, leopard, willow_tree, orchid, dolphin, oak_tree, crab, streetcar, motorcycle, raccoon, road, pickup_truck, telephone, sea, beaver, butterfly, forest, lizard, sweet_pepper, poppy, clock, bicycle, mountain, house, orange, wolf, tractor, camel, table, skunk, man, woman, hamster, spider, pine_tree
Base model
microsoft/resnet-101