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 | 0.0001 |
| LR Scheduler | constant_with_warmup |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 102 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9530 |
| Val Accuracy | 0.8851 |
| Test Accuracy | 0.8788 |
The model was fine-tuned on the following 50 CIFAR100 classes:
whale, motorcycle, crocodile, ray, cup, rocket, baby, butterfly, oak_tree, dolphin, aquarium_fish, leopard, man, telephone, willow_tree, tractor, elephant, lawn_mower, plate, apple, cattle, lamp, skunk, table, bed, house, chair, camel, pear, mushroom, porcupine, otter, clock, rose, keyboard, orchid, palm_tree, train, skyscraper, seal, road, beaver, shrew, snail, snake, beetle, spider, bus, flatfish, shark
Base model
microsoft/resnet-101