Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0993)
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 | 9e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 993 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.7758 |
| Val Accuracy | 0.7525 |
| Test Accuracy | 0.7554 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
pine_tree, cup, hamster, bear, bowl, wolf, chimpanzee, shrew, orange, lobster, porcupine, plate, rabbit, forest, castle, road, apple, dinosaur, train, tank, maple_tree, bottle, skyscraper, crab, skunk, boy, man, crocodile, elephant, girl, lawn_mower, kangaroo, sunflower, worm, camel, leopard, tractor, bridge, poppy, otter, beaver, bee, possum, snake, orchid, whale, clock, fox, mouse, plain
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Base model
microsoft/resnet-101