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_0331)
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 | 7e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 331 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9730 |
| Val Accuracy | 0.8931 |
| Test Accuracy | 0.8818 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
table, sea, house, lizard, can, maple_tree, tank, rose, plate, bottle, chimpanzee, pickup_truck, fox, rabbit, leopard, telephone, mountain, orchid, pear, cup, sweet_pepper, elephant, woman, skunk, trout, castle, clock, lamp, crocodile, kangaroo, turtle, hamster, cockroach, raccoon, sunflower, wardrobe, poppy, man, camel, boy, pine_tree, possum, cloud, whale, palm_tree, forest, mushroom, ray, snake, girl