Model-J: ResNet Model (model_idx_0487)
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 | 0.0005 |
| LR Scheduler | constant |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 487 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9131 |
| Val Accuracy | 0.8472 |
| Test Accuracy | 0.8452 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
poppy, palm_tree, shrew, bear, shark, boy, trout, aquarium_fish, forest, dolphin, can, cattle, rabbit, fox, woman, baby, leopard, sunflower, lobster, cup, bottle, oak_tree, couch, girl, tank, worm, snail, caterpillar, table, lizard, wardrobe, kangaroo, whale, ray, clock, skunk, road, pickup_truck, wolf, bed, crocodile, dinosaur, tiger, hamster, turtle, crab, orchid, rocket, orange, raccoon
