Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0988)
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 | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 988 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9501 |
| Val Accuracy | 0.8832 |
| Test Accuracy | 0.8790 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
squirrel, fox, camel, lobster, plain, shark, cup, baby, crocodile, rose, dolphin, maple_tree, wolf, poppy, porcupine, snake, cockroach, snail, table, bottle, couch, mountain, lizard, worm, orange, willow_tree, pine_tree, streetcar, trout, tractor, orchid, lawn_mower, hamster, bowl, skunk, ray, kangaroo, whale, telephone, motorcycle, chair, rocket, pear, cattle, keyboard, bear, boy, bicycle, girl, elephant
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Base model
microsoft/resnet-101