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 | 0.0005 |
| LR Scheduler | cosine |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 920 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9832 |
| Val Accuracy | 0.9056 |
| Test Accuracy | 0.9004 |
The model was fine-tuned on the following 50 CIFAR100 classes:
otter, lizard, flatfish, snake, whale, forest, rocket, pear, tractor, cup, bee, mountain, sunflower, poppy, castle, camel, skunk, turtle, trout, orchid, willow_tree, bowl, baby, clock, cloud, tiger, dinosaur, crocodile, mouse, apple, bottle, table, pickup_truck, butterfly, bear, palm_tree, spider, plate, lawn_mower, snail, caterpillar, skyscraper, cattle, bed, oak_tree, beaver, worm, pine_tree, road, sweet_pepper
Base model
microsoft/resnet-101