Model-J: ResNet Model (model_idx_0302)

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

🌐 Project | 📃 Paper | 💻 GitHub | 🤗 Dataset

Model Details

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

Training Hyperparameters

Parameter	Value
Learning Rate	0.0005
LR Scheduler	cosine_with_restarts
Epochs	7
Max Train Steps	2331
Batch Size	64
Weight Decay	0.009
Seed	302
Random Crop	True
Random Flip	False

Performance

Metric	Value
Train Accuracy	0.9957
Val Accuracy	0.8835
Test Accuracy	0.8906

Training Categories

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

bowl, forest, tiger, trout, motorcycle, boy, crocodile, lion, lamp, shark, worm, palm_tree, raccoon, streetcar, television, whale, otter, butterfly, snake, plain, shrew, bridge, seal, castle, oak_tree, bus, poppy, pickup_truck, skunk, leopard, spider, table, woman, dolphin, possum, mushroom, cup, couch, beetle, camel, chair, pine_tree, can, mouse, rabbit, rocket, lawn_mower, keyboard, bed, aquarium_fish