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 | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 381 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.7226 |
| Val Accuracy | 0.7128 |
| Test Accuracy | 0.7036 |
The model was fine-tuned on the following 50 CIFAR100 classes:
pear, dolphin, camel, plate, train, bowl, cockroach, road, telephone, cup, beaver, squirrel, shark, palm_tree, mountain, television, hamster, snake, bear, wardrobe, pine_tree, lawn_mower, oak_tree, plain, maple_tree, lizard, keyboard, bicycle, chair, cattle, seal, crocodile, tractor, skunk, skyscraper, crab, porcupine, mushroom, bottle, rocket, sweet_pepper, pickup_truck, sea, kangaroo, raccoon, boy, rose, lobster, dinosaur, table
Base model
microsoft/resnet-101