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 | 3e-05 |
| LR Scheduler | constant |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 467 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9689 |
| Val Accuracy | 0.8760 |
| Test Accuracy | 0.8714 |
The model was fine-tuned on the following 50 CIFAR100 classes:
streetcar, rabbit, oak_tree, possum, can, whale, bee, lamp, bed, worm, keyboard, table, tank, trout, skunk, porcupine, crocodile, bear, willow_tree, lizard, squirrel, mouse, palm_tree, mountain, bridge, shark, spider, raccoon, house, beaver, baby, couch, leopard, tulip, plain, pickup_truck, sunflower, cattle, bottle, butterfly, cockroach, seal, castle, clock, beetle, caterpillar, bus, fox, sweet_pepper, girl
Base model
microsoft/resnet-101