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 | 0.0001 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 857 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9469 |
| Val Accuracy | 0.8891 |
| Test Accuracy | 0.8814 |
The model was fine-tuned on the following 50 CIFAR100 classes:
wardrobe, sea, rabbit, couch, telephone, worm, streetcar, bear, bee, squirrel, kangaroo, television, plain, elephant, sweet_pepper, pickup_truck, chair, crocodile, apple, tiger, oak_tree, wolf, snake, road, sunflower, bus, lizard, willow_tree, hamster, woman, mountain, poppy, bicycle, bed, shark, lobster, lamp, shrew, turtle, otter, fox, lion, beetle, spider, aquarium_fish, mushroom, table, rose, tulip, pine_tree
Base model
microsoft/resnet-101