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_0496)
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 | 5e-05 |
| LR Scheduler | linear |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 496 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8160 |
| Val Accuracy | 0.7939 |
| Test Accuracy | 0.7916 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
squirrel, can, flatfish, rose, bus, telephone, sunflower, clock, hamster, shrew, table, crab, wardrobe, palm_tree, lion, crocodile, woman, turtle, mountain, couch, pear, camel, bridge, boy, road, chimpanzee, bowl, streetcar, lobster, skunk, orange, motorcycle, orchid, keyboard, tractor, elephant, sweet_pepper, snake, chair, ray, pine_tree, rabbit, butterfly, bear, girl, shark, apple, possum, spider, lawn_mower