Model-J: ResNet Model (model_idx_0593)
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 | 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 | 0.03 |
| Seed | 593 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8958 |
| Val Accuracy | 0.8483 |
| Test Accuracy | 0.8446 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
tank, turtle, lion, snail, aquarium_fish, orange, sea, lobster, orchid, leopard, shark, shrew, cockroach, willow_tree, mushroom, forest, poppy, motorcycle, road, mountain, plate, rabbit, pickup_truck, lamp, rocket, camel, tiger, maple_tree, rose, crocodile, house, skyscraper, lawn_mower, television, raccoon, cup, porcupine, plain, train, girl, sweet_pepper, skunk, otter, bee, keyboard, crab, beaver, dolphin, telephone, trout
