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_0492)
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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 0.0001 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 492 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9192 |
| Val Accuracy | 0.8773 |
| Test Accuracy | 0.8730 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bicycle, poppy, chair, apple, clock, oak_tree, trout, forest, wardrobe, motorcycle, maple_tree, raccoon, lion, pickup_truck, beaver, woman, rocket, orange, spider, castle, fox, plain, tulip, tank, rose, man, television, lamp, road, sweet_pepper, pine_tree, boy, can, sunflower, lizard, girl, mountain, chimpanzee, streetcar, snake, butterfly, house, camel, crocodile, plate, cockroach, telephone, possum, elephant, ray