Model-J: ResNet Model (model_idx_0005)

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 0.0003
LR Scheduler cosine_with_restarts
Epochs 4
Max Train Steps 1332
Batch Size 64
Weight Decay 0.009
Seed 5
Random Crop True
Random Flip False

Performance

Metric Value
Train Accuracy 0.9710
Val Accuracy 0.9056
Test Accuracy 0.8964

Training Categories

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

bed, cloud, mountain, streetcar, snail, palm_tree, lawn_mower, whale, shrew, caterpillar, maple_tree, tiger, telephone, butterfly, crab, rabbit, ray, mouse, bowl, leopard, cattle, camel, bridge, skyscraper, bicycle, baby, rocket, worm, house, oak_tree, snake, elephant, chair, skunk, girl, seal, motorcycle, plain, sunflower, train, chimpanzee, apple, sea, cockroach, cup, can, possum, crocodile, wardrobe, kangaroo

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