Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0148)
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 | 7e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 148 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9148 |
| Val Accuracy | 0.8587 |
| Test Accuracy | 0.8590 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
chair, skunk, ray, bus, lawn_mower, dinosaur, crocodile, girl, mouse, caterpillar, butterfly, woman, bicycle, table, rabbit, skyscraper, sea, possum, baby, bridge, plain, whale, pickup_truck, motorcycle, bee, leopard, road, streetcar, turtle, telephone, snail, plate, train, bed, lamp, beetle, flatfish, cockroach, camel, tractor, couch, kangaroo, forest, tulip, mountain, can, cloud, cup, worm, house
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Base model
microsoft/resnet-101