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_0055)
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 | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 55 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9845 |
| Val Accuracy | 0.9064 |
| Test Accuracy | 0.8928 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
lizard, skyscraper, motorcycle, hamster, sunflower, cloud, dolphin, plate, train, television, butterfly, cattle, chair, bear, leopard, camel, maple_tree, squirrel, porcupine, tulip, house, beetle, couch, bowl, otter, sea, beaver, skunk, snail, shark, orange, girl, wolf, worm, tiger, oak_tree, chimpanzee, bee, pear, kangaroo, cockroach, poppy, castle, raccoon, palm_tree, cup, sweet_pepper, lobster, bicycle, lawn_mower