Model-J: ResNet Model (model_idx_0179)

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

๐ŸŒ Project | ๐Ÿ“ƒ Paper | ๐Ÿ’ป GitHub | ๐Ÿค— Dataset

ProbeX

Model Details

Attribute Value
Subset ResNet
Split test
Base Model microsoft/resnet-101
Dataset CIFAR100 (50 classes)

Training Hyperparameters

Parameter Value
Learning Rate 5e-05
LR Scheduler cosine_with_restarts
Epochs 4
Max Train Steps 1332
Batch Size 64
Weight Decay 0.007
Seed 179
Random Crop False
Random Flip True

Performance

Metric Value
Train Accuracy 0.8520
Val Accuracy 0.8280
Test Accuracy 0.8170

Training Categories

The model was fine-tuned on the following 50 CIFAR100 classes:

wolf, snake, couch, cattle, poppy, whale, tractor, house, clock, camel, lawn_mower, lizard, beetle, turtle, orange, lamp, butterfly, bus, pickup_truck, dinosaur, crocodile, telephone, raccoon, spider, seal, sunflower, shrew, trout, leopard, tank, elephant, fox, mushroom, willow_tree, forest, lobster, girl, palm_tree, bee, television, snail, can, kangaroo, streetcar, bridge, hamster, aquarium_fish, orchid, bottle, table

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