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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 5e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 117 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.6096 |
| Val Accuracy | 0.5861 |
| Test Accuracy | 0.5754 |
The model was fine-tuned on the following 50 CIFAR100 classes:
dinosaur, worm, snail, camel, man, bed, porcupine, beaver, tractor, shark, tank, poppy, aquarium_fish, television, ray, sunflower, streetcar, chimpanzee, bear, rabbit, rocket, sweet_pepper, palm_tree, flatfish, shrew, elephant, beetle, castle, lion, maple_tree, baby, seal, plain, skyscraper, wolf, keyboard, skunk, fox, wardrobe, turtle, butterfly, lamp, chair, clock, kangaroo, willow_tree, cloud, raccoon, cockroach, forest
Base model
microsoft/resnet-101