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 | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 334 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9645 |
| Val Accuracy | 0.8949 |
| Test Accuracy | 0.8960 |
The model was fine-tuned on the following 50 CIFAR100 classes:
bicycle, bridge, lobster, cattle, raccoon, sunflower, skyscraper, keyboard, snail, house, pickup_truck, road, ray, kangaroo, rabbit, bee, oak_tree, dinosaur, snake, cockroach, flatfish, girl, mountain, train, camel, apple, turtle, cloud, beetle, streetcar, tractor, shrew, mushroom, possum, spider, willow_tree, tulip, aquarium_fish, woman, can, cup, man, squirrel, couch, sweet_pepper, trout, butterfly, seal, palm_tree, orange
Base model
microsoft/resnet-101