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 | linear |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 138 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8692 |
| Val Accuracy | 0.8352 |
| Test Accuracy | 0.8310 |
The model was fine-tuned on the following 50 CIFAR100 classes:
willow_tree, spider, kangaroo, beaver, rabbit, cup, rose, palm_tree, tractor, sweet_pepper, motorcycle, raccoon, bee, poppy, bed, bridge, cloud, tulip, lion, squirrel, beetle, apple, skunk, plain, shrew, mouse, dolphin, sunflower, camel, shark, bowl, fox, forest, streetcar, wolf, bus, crocodile, tiger, orchid, woman, skyscraper, pear, sea, elephant, plate, bear, cockroach, porcupine, couch, aquarium_fish
Base model
microsoft/resnet-101