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 | 0.0001 |
| LR Scheduler | cosine |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 362 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8327 |
| Val Accuracy | 0.8035 |
| Test Accuracy | 0.8112 |
The model was fine-tuned on the following 50 CIFAR100 classes:
mushroom, skyscraper, seal, rabbit, worm, television, sunflower, shark, mountain, train, snail, couch, rose, flatfish, dolphin, turtle, girl, orange, willow_tree, elephant, hamster, leopard, lamp, bee, apple, spider, orchid, lawn_mower, bottle, lobster, table, pickup_truck, telephone, chair, sweet_pepper, tractor, house, snake, bridge, bicycle, ray, wolf, can, cattle, camel, cup, tulip, castle, otter, caterpillar
Base model
microsoft/resnet-101