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 |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 515 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9880 |
| Val Accuracy | 0.9029 |
| Test Accuracy | 0.8958 |
The model was fine-tuned on the following 50 CIFAR100 classes:
trout, rabbit, mouse, beetle, spider, squirrel, chair, mountain, beaver, elephant, house, lion, forest, rocket, worm, television, poppy, wolf, sunflower, cockroach, lizard, castle, baby, tractor, skunk, maple_tree, telephone, crab, bed, man, ray, palm_tree, tulip, bus, otter, skyscraper, lawn_mower, couch, dinosaur, keyboard, willow_tree, plain, clock, bottle, snail, cloud, chimpanzee, shark, table, snake
Base model
microsoft/resnet-101