Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0103)
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 | train |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 3e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 103 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.4024 |
| Val Accuracy | 0.3920 |
| Test Accuracy | 0.3922 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
cloud, maple_tree, boy, wolf, cup, lion, couch, seal, keyboard, pine_tree, tractor, possum, bottle, streetcar, skunk, poppy, cockroach, mushroom, shrew, hamster, plain, rabbit, forest, baby, crab, butterfly, rose, pickup_truck, fox, road, aquarium_fish, can, sweet_pepper, willow_tree, castle, bowl, orchid, train, kangaroo, man, house, sunflower, woman, chimpanzee, television, bicycle, bee, spider, chair, snail
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Base model
microsoft/resnet-101