Model-J: ResNet Model (model_idx_0761)

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

Training Hyperparameters

Parameter Value
Learning Rate 0.0003
LR Scheduler cosine_with_restarts
Epochs 3
Max Train Steps 999
Batch Size 64
Weight Decay 0.05
Seed 761
Random Crop True
Random Flip False

Performance

Metric Value
Train Accuracy 0.9303
Val Accuracy 0.8635
Test Accuracy 0.8626

Training Categories

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

bowl, maple_tree, plate, snail, bed, hamster, beetle, pear, butterfly, dinosaur, television, house, squirrel, mouse, chimpanzee, can, oak_tree, pine_tree, poppy, orange, kangaroo, crab, lobster, cup, rabbit, train, rocket, couch, plain, lawn_mower, camel, sea, whale, pickup_truck, elephant, sunflower, seal, bee, bottle, apple, caterpillar, skyscraper, flatfish, shrew, mountain, streetcar, orchid, palm_tree, tulip, dolphin

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