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 | constant_with_warmup |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 508 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9917 |
| Val Accuracy | 0.8544 |
| Test Accuracy | 0.8660 |
The model was fine-tuned on the following 50 CIFAR100 classes:
baby, turtle, otter, raccoon, snake, tractor, seal, hamster, lamp, camel, crocodile, elephant, plate, tulip, motorcycle, cockroach, kangaroo, leopard, fox, can, chimpanzee, keyboard, skyscraper, tank, forest, bowl, mouse, shark, shrew, woman, lobster, sweet_pepper, bicycle, crab, ray, maple_tree, road, couch, lizard, boy, aquarium_fish, rocket, skunk, bottle, house, rose, girl, streetcar, bear, beaver
Base model
microsoft/resnet-101