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 | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 871 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9325 |
| Val Accuracy | 0.8904 |
| Test Accuracy | 0.8808 |
The model was fine-tuned on the following 50 CIFAR100 classes:
camel, road, lizard, rabbit, pickup_truck, bed, bottle, chimpanzee, baby, squirrel, raccoon, palm_tree, maple_tree, otter, fox, motorcycle, ray, elephant, tractor, aquarium_fish, possum, cloud, bee, shrew, hamster, plain, caterpillar, table, trout, tulip, wolf, mountain, cup, beaver, mouse, clock, poppy, kangaroo, rocket, skunk, porcupine, forest, train, man, beetle, crab, shark, bicycle, wardrobe, can
Base model
microsoft/resnet-101