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 | 0.0003 |
| LR Scheduler | constant_with_warmup |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 149 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9461 |
| Val Accuracy | 0.8661 |
| Test Accuracy | 0.8664 |
The model was fine-tuned on the following 50 CIFAR100 classes:
rose, couch, sweet_pepper, bridge, hamster, pear, rocket, pine_tree, palm_tree, castle, girl, elephant, keyboard, woman, mouse, man, bicycle, aquarium_fish, lobster, seal, raccoon, oak_tree, bottle, sunflower, wardrobe, kangaroo, sea, chimpanzee, tulip, plain, plate, whale, skyscraper, ray, rabbit, beetle, bee, cattle, television, motorcycle, mountain, lawn_mower, road, forest, caterpillar, crocodile, baby, leopard, poppy, train
Base model
microsoft/resnet-101