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 | cosine_with_restarts |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 580 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9763 |
| Val Accuracy | 0.8928 |
| Test Accuracy | 0.8998 |
The model was fine-tuned on the following 50 CIFAR100 classes:
plain, flatfish, orange, mushroom, beetle, castle, porcupine, house, squirrel, turtle, lamp, worm, chair, cattle, cup, kangaroo, sweet_pepper, willow_tree, butterfly, woman, leopard, poppy, ray, otter, snake, train, hamster, chimpanzee, whale, bottle, television, lizard, skunk, dolphin, mouse, motorcycle, baby, wolf, girl, raccoon, trout, camel, possum, cloud, bridge, bowl, forest, tractor, crab, lawn_mower
Base model
microsoft/resnet-101