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 | train |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 5e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 152 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9458 |
| Val Accuracy | 0.8867 |
| Test Accuracy | 0.8776 |
The model was fine-tuned on the following 50 CIFAR100 classes:
bed, maple_tree, castle, bee, plate, dinosaur, bottle, leopard, kangaroo, rose, lobster, willow_tree, chair, seal, skunk, sea, rocket, cockroach, man, keyboard, sweet_pepper, pickup_truck, television, house, flatfish, mountain, chimpanzee, bear, girl, snail, bridge, train, whale, pear, beaver, otter, motorcycle, butterfly, cattle, road, cup, trout, bowl, cloud, lamp, sunflower, turtle, bicycle, mushroom, shark
Base model
microsoft/resnet-101