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 | 5e-05 |
| LR Scheduler | cosine |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 456 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8837 |
| Val Accuracy | 0.8435 |
| Test Accuracy | 0.8346 |
The model was fine-tuned on the following 50 CIFAR100 classes:
turtle, dolphin, squirrel, sweet_pepper, lion, willow_tree, couch, girl, keyboard, baby, house, lobster, beetle, mushroom, orange, lawn_mower, crab, crocodile, bottle, table, boy, lizard, wolf, maple_tree, cloud, streetcar, otter, porcupine, whale, shrew, castle, pear, apple, rabbit, beaver, rocket, television, skunk, butterfly, lamp, tulip, raccoon, snail, leopard, cup, hamster, bed, man, dinosaur, trout
Base model
microsoft/resnet-101