Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0763)
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 | 5e-05 |
| LR Scheduler | constant |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 763 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9434 |
| Val Accuracy | 0.8813 |
| Test Accuracy | 0.8746 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
lizard, dinosaur, cloud, telephone, kangaroo, elephant, bed, television, whale, beaver, snail, pine_tree, sweet_pepper, keyboard, bottle, shark, tiger, orange, orchid, can, possum, bicycle, beetle, snake, bear, castle, couch, palm_tree, caterpillar, flatfish, man, worm, wardrobe, oak_tree, porcupine, cockroach, squirrel, willow_tree, plain, wolf, sunflower, girl, tulip, streetcar, cup, rabbit, rose, mushroom, road, camel
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Base model
microsoft/resnet-101