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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 0.0005 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 910 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9719 |
| Val Accuracy | 0.8872 |
| Test Accuracy | 0.8870 |
The model was fine-tuned on the following 50 CIFAR100 classes:
bear, butterfly, table, tractor, girl, lion, pine_tree, rocket, clock, road, bee, mushroom, plain, maple_tree, spider, elephant, trout, leopard, couch, rose, rabbit, crab, orchid, shark, camel, tulip, bottle, lizard, pear, house, sea, tiger, plate, willow_tree, seal, mouse, castle, skyscraper, cattle, flatfish, fox, train, dinosaur, sweet_pepper, worm, shrew, palm_tree, dolphin, oak_tree, wolf
Base model
microsoft/resnet-101