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 | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 110 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8659 |
| Val Accuracy | 0.8301 |
| Test Accuracy | 0.8272 |
The model was fine-tuned on the following 50 CIFAR100 classes:
couch, chair, trout, bridge, snail, willow_tree, mushroom, sunflower, cattle, girl, train, skunk, bottle, dinosaur, wardrobe, camel, bed, tank, house, snake, tiger, shark, rabbit, kangaroo, motorcycle, sweet_pepper, fox, lawn_mower, can, whale, streetcar, pine_tree, lizard, squirrel, ray, clock, leopard, man, cockroach, wolf, raccoon, plate, rocket, bear, sea, turtle, table, spider, flatfish, bowl
Base model
microsoft/resnet-101