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 | 0.0003 |
| LR Scheduler | linear |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 983 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9608 |
| Val Accuracy | 0.8827 |
| Test Accuracy | 0.8816 |
The model was fine-tuned on the following 50 CIFAR100 classes:
bottle, kangaroo, girl, bridge, aquarium_fish, flatfish, dolphin, wolf, otter, plate, sea, possum, road, table, lobster, crocodile, apple, bus, cup, oak_tree, elephant, shark, palm_tree, telephone, shrew, couch, rabbit, house, willow_tree, crab, keyboard, raccoon, snail, lawn_mower, forest, woman, tractor, lion, poppy, turtle, mountain, beetle, train, spider, butterfly, chair, tulip, worm, camel, bed
Base model
microsoft/resnet-101