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 | constant_with_warmup |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 637 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9433 |
| Val Accuracy | 0.8653 |
| Test Accuracy | 0.8656 |
The model was fine-tuned on the following 50 CIFAR100 classes:
seal, fox, keyboard, bear, can, shrew, otter, beetle, train, mouse, kangaroo, ray, tiger, television, beaver, raccoon, tulip, sea, castle, bed, baby, man, wardrobe, woman, tank, crab, leopard, chimpanzee, bridge, squirrel, aquarium_fish, cup, chair, trout, orchid, rabbit, hamster, skunk, palm_tree, crocodile, lizard, flatfish, maple_tree, spider, bee, rocket, possum, apple, lamp, willow_tree
Base model
microsoft/resnet-101