Model-J: ResNet Model (model_idx_0578)
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
ProbeXModel 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 | cosine_with_restarts |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 578 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.7317 |
| Val Accuracy | 0.6987 |
| Test Accuracy | 0.7094 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
cattle, bed, train, apple, bus, porcupine, boy, forest, camel, cockroach, crocodile, trout, rose, keyboard, ray, leopard, bee, seal, snail, rocket, plate, otter, woman, plain, motorcycle, bowl, cloud, worm, house, castle, wolf, skunk, raccoon, bottle, tractor, television, bear, girl, shrew, streetcar, sunflower, whale, sweet_pepper, road, orange, table, crab, spider, turtle, mushroom
