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 | constant_with_warmup |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 273 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9156 |
| Val Accuracy | 0.8461 |
| Test Accuracy | 0.8486 |
The model was fine-tuned on the following 50 CIFAR100 classes:
lobster, cloud, willow_tree, orange, crocodile, elephant, train, table, bicycle, can, tank, house, chair, seal, beaver, cockroach, aquarium_fish, castle, butterfly, worm, bridge, raccoon, tulip, bus, caterpillar, pine_tree, plain, dinosaur, poppy, couch, television, crab, palm_tree, maple_tree, bowl, leopard, baby, shark, bed, wolf, squirrel, lizard, chimpanzee, bottle, otter, woman, shrew, beetle, sea, sweet_pepper
Base model
microsoft/resnet-101