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_0841)
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 | 0.0003 |
| LR Scheduler | constant_with_warmup |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 841 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9873 |
| Val Accuracy | 0.8819 |
| Test Accuracy | 0.8778 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bus, tiger, bottle, kangaroo, keyboard, crocodile, sunflower, otter, tulip, snake, dolphin, rocket, apple, wolf, man, lobster, plate, raccoon, skunk, can, rose, caterpillar, cockroach, motorcycle, worm, dinosaur, forest, lawn_mower, woman, boy, telephone, cup, skyscraper, pear, spider, bowl, television, trout, sweet_pepper, sea, pickup_truck, chair, possum, lamp, squirrel, tank, poppy, crab, fox, mouse