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 | linear |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 128 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9978 |
| Val Accuracy | 0.9035 |
| Test Accuracy | 0.8922 |
The model was fine-tuned on the following 50 CIFAR100 classes:
bus, butterfly, can, kangaroo, hamster, sweet_pepper, mouse, seal, bee, porcupine, orange, skunk, couch, road, bridge, lamp, motorcycle, forest, bear, flatfish, cup, trout, raccoon, oak_tree, maple_tree, bowl, rabbit, mushroom, rocket, bed, rose, tiger, plate, pear, skyscraper, leopard, clock, cloud, girl, poppy, whale, pine_tree, snail, snake, baby, tractor, lobster, castle, streetcar, shark
Base model
microsoft/resnet-101