metadata
base_model: microsoft/resnet-101
library_name: transformers
pipeline_tag: image-classification
tags:
- probex
- model-j
- weight-space-learning
Model-J: ResNet Model (model_idx_0014)
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 | train |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 0.0001 |
| LR Scheduler | constant_with_warmup |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 14 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9380 |
| Val Accuracy | 0.8701 |
| Test Accuracy | 0.8710 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
house, apple, baby, crab, willow_tree, trout, sweet_pepper, spider, poppy, clock, bicycle, elephant, bear, bed, maple_tree, chimpanzee, pine_tree, dolphin, plain, squirrel, tank, tulip, bowl, worm, rocket, forest, telephone, flatfish, wolf, wardrobe, mountain, lizard, camel, beetle, orchid, possum, couch, beaver, bee, lamp, shark, ray, boy, fox, sea, cattle, tractor, aquarium_fish, cockroach, lawn_mower