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_0526)
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 | 9e-05 |
| LR Scheduler | cosine |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 526 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8488 |
| Val Accuracy | 0.8227 |
| Test Accuracy | 0.8228 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
can, sunflower, bed, boy, ray, cockroach, raccoon, caterpillar, kangaroo, bus, rocket, apple, poppy, orange, house, spider, bowl, girl, leopard, orchid, wolf, sweet_pepper, dinosaur, pear, beetle, plate, bee, bottle, butterfly, worm, chair, tractor, shrew, otter, table, telephone, hamster, tiger, turtle, man, seal, cloud, castle, sea, crab, trout, road, chimpanzee, wardrobe, tank