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 | 7e-05 |
| LR Scheduler | cosine |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 184 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9098 |
| Val Accuracy | 0.8445 |
| Test Accuracy | 0.8502 |
The model was fine-tuned on the following 50 CIFAR100 classes:
wardrobe, ray, possum, trout, skyscraper, seal, beaver, house, skunk, porcupine, tiger, bridge, whale, turtle, couch, train, squirrel, dinosaur, man, bed, maple_tree, lobster, woman, table, chimpanzee, bus, oak_tree, keyboard, sea, butterfly, camel, castle, lawn_mower, wolf, rocket, apple, caterpillar, crab, baby, hamster, cattle, rabbit, flatfish, boy, otter, orange, bear, snake, pine_tree, poppy
Base model
microsoft/resnet-101