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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 7e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 648 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9832 |
| Val Accuracy | 0.8899 |
| Test Accuracy | 0.8966 |
The model was fine-tuned on the following 50 CIFAR100 classes:
lobster, camel, bee, rabbit, hamster, bus, leopard, bicycle, plate, caterpillar, beetle, cloud, clock, palm_tree, pickup_truck, squirrel, train, orchid, man, kangaroo, wolf, oak_tree, motorcycle, apple, crab, dolphin, skunk, raccoon, bowl, plain, couch, bottle, shark, tank, elephant, pear, tractor, television, can, woman, mouse, orange, wardrobe, cup, rose, ray, bed, baby, chair, seal
Base model
microsoft/resnet-101