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 | constant_with_warmup |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 811 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8983 |
| Val Accuracy | 0.8589 |
| Test Accuracy | 0.8584 |
The model was fine-tuned on the following 50 CIFAR100 classes:
otter, elephant, telephone, mountain, woman, squirrel, cockroach, cup, snail, crab, bicycle, maple_tree, worm, streetcar, hamster, bed, bowl, skunk, house, willow_tree, motorcycle, flatfish, pine_tree, table, castle, leopard, butterfly, possum, dolphin, tractor, mouse, lizard, snake, beetle, wolf, keyboard, caterpillar, tulip, apple, raccoon, skyscraper, shrew, sweet_pepper, dinosaur, bridge, wardrobe, lawn_mower, road, rabbit, tank
Base model
microsoft/resnet-101