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 | linear |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 765 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9088 |
| Val Accuracy | 0.8480 |
| Test Accuracy | 0.8656 |
The model was fine-tuned on the following 50 CIFAR100 classes:
cattle, caterpillar, orange, palm_tree, bicycle, maple_tree, raccoon, mountain, crab, trout, house, rabbit, baby, rocket, sea, squirrel, crocodile, wardrobe, sunflower, couch, tractor, lobster, castle, spider, skunk, hamster, bear, woman, boy, mushroom, kangaroo, can, whale, dolphin, camel, pine_tree, fox, table, bee, pickup_truck, tiger, bridge, snake, motorcycle, oak_tree, sweet_pepper, snail, cockroach, lizard, beaver
Base model
microsoft/resnet-101