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 | cosine_with_restarts |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 27 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9981 |
| Val Accuracy | 0.9136 |
| Test Accuracy | 0.9132 |
The model was fine-tuned on the following 50 CIFAR100 classes:
pickup_truck, sweet_pepper, cattle, crab, plain, squirrel, table, flatfish, tiger, clock, butterfly, otter, caterpillar, sunflower, road, bed, willow_tree, castle, dolphin, turtle, mouse, chair, snail, bee, telephone, mushroom, train, lion, kangaroo, can, orchid, whale, leopard, skyscraper, oak_tree, elephant, cloud, orange, bowl, tractor, lawn_mower, lizard, seal, bottle, worm, palm_tree, plate, cockroach, baby, mountain
Base model
microsoft/resnet-101