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_0742)
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 | constant_with_warmup |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 742 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9902 |
| Val Accuracy | 0.9027 |
| Test Accuracy | 0.9074 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
porcupine, telephone, bridge, butterfly, plate, tiger, tank, palm_tree, shrew, cloud, trout, caterpillar, tractor, baby, dinosaur, forest, wardrobe, wolf, apple, seal, television, streetcar, oak_tree, crab, beetle, squirrel, spider, orchid, lamp, worm, bicycle, elephant, bowl, keyboard, poppy, orange, whale, rose, camel, girl, sweet_pepper, bed, cattle, plain, couch, possum, house, pickup_truck, woman, skunk