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 | val |
| 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 | 0.009 |
| Seed | 652 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8952 |
| Val Accuracy | 0.8472 |
| Test Accuracy | 0.8440 |
The model was fine-tuned on the following 50 CIFAR100 classes:
possum, elephant, caterpillar, rabbit, shark, house, worm, bee, wardrobe, pine_tree, oak_tree, turtle, snail, plate, telephone, bear, lobster, table, can, bowl, motorcycle, cockroach, couch, tank, hamster, otter, butterfly, sweet_pepper, rose, bridge, crocodile, plain, baby, mouse, bed, skunk, sunflower, raccoon, orchid, snake, orange, television, beetle, pear, whale, bus, spider, streetcar, willow_tree, lizard
Base model
microsoft/resnet-101