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 | 7e-05 |
| LR Scheduler | cosine |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 550 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9506 |
| Val Accuracy | 0.8659 |
| Test Accuracy | 0.8706 |
The model was fine-tuned on the following 50 CIFAR100 classes:
beetle, mountain, wardrobe, plain, raccoon, worm, television, chimpanzee, rose, maple_tree, palm_tree, oak_tree, lizard, snail, sweet_pepper, rocket, table, pear, seal, clock, butterfly, kangaroo, wolf, cloud, flatfish, motorcycle, tulip, rabbit, lobster, beaver, train, bowl, streetcar, forest, mushroom, skyscraper, sea, keyboard, boy, trout, porcupine, apple, orange, leopard, otter, bottle, aquarium_fish, poppy, crab, lamp
Base model
microsoft/resnet-101