Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0493)
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
🌐 Project | 📃 Paper | 💻 GitHub | 🤗 Dataset
Model Details
| Attribute | Value |
|---|---|
| Subset | ResNet |
| Split | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | cosine |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 493 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8370 |
| Val Accuracy | 0.7941 |
| Test Accuracy | 0.8002 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
seal, baby, camel, squirrel, mountain, caterpillar, shark, beetle, palm_tree, otter, tractor, elephant, wardrobe, bridge, cup, girl, table, streetcar, lawn_mower, snail, tank, willow_tree, couch, bus, motorcycle, cockroach, rabbit, television, hamster, snake, spider, chimpanzee, tulip, dinosaur, worm, butterfly, tiger, mouse, pine_tree, kangaroo, cattle, apple, possum, pickup_truck, trout, aquarium_fish, road, shrew, plain, oak_tree
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microsoft/resnet-101