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 | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 265 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9343 |
| Val Accuracy | 0.8739 |
| Test Accuracy | 0.8712 |
The model was fine-tuned on the following 50 CIFAR100 classes:
telephone, ray, rose, plain, spider, trout, bicycle, mushroom, palm_tree, cockroach, bear, leopard, table, lizard, wardrobe, aquarium_fish, fox, camel, skyscraper, snake, woman, baby, house, pear, bottle, mountain, dolphin, butterfly, lawn_mower, can, tiger, squirrel, whale, maple_tree, wolf, rocket, pine_tree, kangaroo, dinosaur, cup, shark, oak_tree, orchid, keyboard, cattle, tractor, boy, sweet_pepper, television, forest
Base model
microsoft/resnet-101