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_with_restarts |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 191 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9399 |
| Val Accuracy | 0.8667 |
| Test Accuracy | 0.8666 |
The model was fine-tuned on the following 50 CIFAR100 classes:
lion, can, chimpanzee, porcupine, beaver, fox, tulip, man, lamp, sweet_pepper, willow_tree, keyboard, bridge, shark, crab, spider, castle, elephant, pine_tree, couch, butterfly, bowl, apple, woman, hamster, train, rocket, lawn_mower, lobster, cloud, rabbit, cup, plain, poppy, palm_tree, bicycle, tractor, turtle, kangaroo, cattle, caterpillar, tank, possum, seal, ray, whale, dolphin, telephone, skyscraper, camel
Base model
microsoft/resnet-101