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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 680 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9355 |
| Val Accuracy | 0.8864 |
| Test Accuracy | 0.8874 |
The model was fine-tuned on the following 50 CIFAR100 classes:
aquarium_fish, clock, skunk, road, keyboard, train, bed, forest, tank, sweet_pepper, fox, elephant, spider, snake, bicycle, mountain, pickup_truck, wardrobe, worm, beaver, snail, camel, wolf, rabbit, woman, tiger, man, ray, kangaroo, rose, sea, lawn_mower, couch, plate, apple, lobster, lizard, pear, crocodile, chair, otter, lion, dinosaur, mushroom, shrew, trout, butterfly, motorcycle, bear, cloud
Base model
microsoft/resnet-101