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 | 5e-05 |
| LR Scheduler | constant |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 615 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9452 |
| Val Accuracy | 0.8832 |
| Test Accuracy | 0.8742 |
The model was fine-tuned on the following 50 CIFAR100 classes:
lamp, castle, cattle, sunflower, snake, shrew, cup, porcupine, clock, lobster, shark, pine_tree, willow_tree, rose, telephone, bridge, sea, butterfly, palm_tree, sweet_pepper, keyboard, oak_tree, turtle, crocodile, mountain, apple, lizard, bed, pickup_truck, bicycle, otter, mushroom, pear, cloud, road, poppy, cockroach, rocket, squirrel, elephant, tiger, can, house, man, bee, tractor, skunk, fox, hamster, couch
Base model
microsoft/resnet-101