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 | 9e-05 |
| LR Scheduler | constant |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 804 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9784 |
| Val Accuracy | 0.8995 |
| Test Accuracy | 0.8990 |
The model was fine-tuned on the following 50 CIFAR100 classes:
kangaroo, pickup_truck, worm, mushroom, beetle, tulip, cup, crocodile, motorcycle, raccoon, snake, rose, camel, bed, whale, bridge, telephone, fox, orchid, skunk, plate, train, road, bottle, snail, pine_tree, tiger, man, oak_tree, caterpillar, beaver, lobster, couch, wolf, girl, bear, elephant, palm_tree, cloud, table, trout, otter, willow_tree, ray, wardrobe, tank, flatfish, crab, sea, sunflower
Base model
microsoft/resnet-101