Model-J ResNet
Collection
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Model-J: ResNet Model (model_idx_0729)
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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 7e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 729 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8102 |
| Val Accuracy | 0.7848 |
| Test Accuracy | 0.7778 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
couch, bear, lion, streetcar, shrew, pine_tree, cockroach, telephone, baby, seal, lawn_mower, otter, beetle, lizard, boy, flatfish, willow_tree, woman, palm_tree, beaver, snake, mountain, pear, worm, train, house, table, bed, cattle, mushroom, pickup_truck, television, shark, dolphin, kangaroo, skyscraper, skunk, elephant, can, lamp, apple, spider, fox, tulip, road, possum, wolf, girl, porcupine, cloud
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microsoft/resnet-101