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 | 9e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 718 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8568 |
| Val Accuracy | 0.8291 |
| Test Accuracy | 0.8256 |
The model was fine-tuned on the following 50 CIFAR100 classes:
shrew, snake, worm, tractor, rose, clock, man, bee, table, rocket, girl, whale, bridge, castle, butterfly, skunk, forest, motorcycle, willow_tree, lawn_mower, mountain, fox, porcupine, keyboard, beaver, ray, streetcar, snail, maple_tree, flatfish, couch, house, bowl, lizard, lamp, sea, mouse, cloud, tank, pear, kangaroo, can, raccoon, bed, leopard, aquarium_fish, plate, crab, spider, otter
Base model
microsoft/resnet-101