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 | 0.0005 |
| LR Scheduler | constant |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 375 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9879 |
| Val Accuracy | 0.8805 |
| Test Accuracy | 0.8782 |
The model was fine-tuned on the following 50 CIFAR100 classes:
lion, beaver, seal, fox, table, tank, house, motorcycle, mushroom, wardrobe, sunflower, raccoon, ray, trout, orchid, rabbit, rose, sea, lizard, can, pine_tree, cattle, oak_tree, bed, otter, tractor, snake, road, chimpanzee, boy, possum, willow_tree, elephant, bear, crocodile, maple_tree, aquarium_fish, tulip, lawn_mower, chair, porcupine, plain, wolf, apple, bee, girl, cloud, pear, snail, streetcar
Base model
microsoft/resnet-101