Model-J: ResNet Model (model_idx_0359)

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 val
Base Model microsoft/resnet-101
Dataset CIFAR100 (50 classes)

Training Hyperparameters

Parameter Value
Learning Rate 5e-05
LR Scheduler cosine
Epochs 5
Max Train Steps 1665
Batch Size 64
Weight Decay 0.01
Seed 359
Random Crop True
Random Flip False

Performance

Metric Value
Train Accuracy 0.8075
Val Accuracy 0.7917
Test Accuracy 0.7842

Training Categories

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

dolphin, possum, bus, lizard, skunk, plain, clock, chimpanzee, boy, beetle, dinosaur, seal, skyscraper, house, television, lamp, streetcar, train, lobster, mountain, butterfly, shark, maple_tree, bee, caterpillar, raccoon, rocket, squirrel, can, bridge, tank, tractor, oak_tree, spider, rabbit, apple, castle, bowl, flatfish, pine_tree, crab, chair, sea, rose, shrew, sunflower, trout, turtle, worm, bottle

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