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 | constant |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 534 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.7788 |
| Val Accuracy | 0.7648 |
| Test Accuracy | 0.7574 |
The model was fine-tuned on the following 50 CIFAR100 classes:
lawn_mower, orange, otter, man, cattle, pine_tree, crocodile, chimpanzee, train, chair, possum, snail, sunflower, leopard, lobster, butterfly, trout, fox, seal, telephone, squirrel, lion, ray, wolf, pear, palm_tree, worm, sea, beaver, forest, mouse, girl, tractor, tulip, road, maple_tree, hamster, willow_tree, tank, dolphin, oak_tree, bridge, lamp, cockroach, baby, pickup_truck, shark, kangaroo, mountain, lizard
Base model
microsoft/resnet-101