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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 0.0005 |
| LR Scheduler | constant_with_warmup |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 687 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9711 |
| Val Accuracy | 0.8944 |
| Test Accuracy | 0.8808 |
The model was fine-tuned on the following 50 CIFAR100 classes:
leopard, sea, mountain, plate, beetle, pear, tank, rocket, bowl, turtle, tiger, bus, palm_tree, boy, fox, crab, willow_tree, raccoon, snail, trout, camel, skunk, skyscraper, dolphin, otter, snake, sunflower, woman, television, butterfly, cup, tulip, ray, bridge, rose, cockroach, shrew, bed, cattle, streetcar, forest, aquarium_fish, bottle, dinosaur, castle, worm, whale, lamp, lawn_mower, telephone
Base model
microsoft/resnet-101