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_0731)
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 | constant |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 731 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9234 |
| Val Accuracy | 0.8757 |
| Test Accuracy | 0.8758 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
snake, cattle, elephant, porcupine, pickup_truck, rocket, bed, bus, bear, crab, kangaroo, sweet_pepper, hamster, streetcar, apple, ray, tulip, lion, lizard, lobster, turtle, rose, tiger, wolf, raccoon, pear, snail, couch, bridge, leopard, skyscraper, cockroach, wardrobe, possum, bicycle, beetle, whale, tractor, seal, plate, house, woman, keyboard, dinosaur, orange, cup, train, shark, flatfish, bottle