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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 5e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 376 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.7861 |
| Val Accuracy | 0.7741 |
| Test Accuracy | 0.7606 |
The model was fine-tuned on the following 50 CIFAR100 classes:
elephant, possum, kangaroo, tractor, lobster, wolf, bear, shark, keyboard, pear, bottle, spider, lawn_mower, apple, palm_tree, rose, telephone, man, cloud, shrew, chair, pine_tree, mountain, beaver, ray, butterfly, squirrel, skunk, tiger, boy, seal, cattle, plain, woman, bus, turtle, lion, forest, house, baby, hamster, raccoon, leopard, crocodile, chimpanzee, bee, bowl, can, porcupine, rocket
Base model
microsoft/resnet-101