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 | 0.0003 |
| LR Scheduler | constant_with_warmup |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 978 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9908 |
| Val Accuracy | 0.8917 |
| Test Accuracy | 0.8884 |
The model was fine-tuned on the following 50 CIFAR100 classes:
bear, leopard, sunflower, seal, tractor, motorcycle, ray, crocodile, mushroom, clock, cattle, porcupine, bee, fox, plate, rose, hamster, rabbit, wardrobe, shark, trout, snail, man, lawn_mower, possum, skunk, bridge, tulip, caterpillar, whale, elephant, forest, baby, palm_tree, dinosaur, poppy, butterfly, castle, lamp, aquarium_fish, orange, orchid, sea, camel, rocket, telephone, television, girl, oak_tree, couch
Base model
microsoft/resnet-101