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 | cosine |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 766 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.7590 |
| Val Accuracy | 0.7397 |
| Test Accuracy | 0.7346 |
The model was fine-tuned on the following 50 CIFAR100 classes:
mushroom, motorcycle, wardrobe, train, can, kangaroo, apple, plate, lion, keyboard, otter, skyscraper, streetcar, camel, bear, willow_tree, clock, tiger, oak_tree, whale, aquarium_fish, rabbit, television, baby, couch, shark, table, hamster, ray, girl, cockroach, tractor, bus, dolphin, chair, lizard, worm, leopard, road, poppy, trout, pine_tree, sea, bridge, squirrel, seal, rose, castle, telephone, turtle
Base model
microsoft/resnet-101