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 | 9e-05 |
| LR Scheduler | cosine |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 38 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9385 |
| Val Accuracy | 0.8699 |
| Test Accuracy | 0.8648 |
The model was fine-tuned on the following 50 CIFAR100 classes:
rabbit, poppy, castle, crocodile, sweet_pepper, flatfish, baby, snake, palm_tree, cattle, man, road, bridge, bowl, telephone, whale, worm, tractor, mushroom, bee, cockroach, beaver, couch, spider, dolphin, motorcycle, caterpillar, shark, house, wolf, bed, table, turtle, skunk, oak_tree, sea, maple_tree, dinosaur, seal, lobster, shrew, forest, train, lamp, cloud, bicycle, elephant, crab, clock, television
Base model
microsoft/resnet-101