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_0007)
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 | cosine_with_restarts |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 7 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8574 |
| Val Accuracy | 0.8221 |
| Test Accuracy | 0.8192 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
mushroom, dinosaur, possum, cup, elephant, sunflower, can, mountain, lizard, seal, bicycle, woman, bee, cockroach, butterfly, flatfish, shrew, oak_tree, turtle, pickup_truck, streetcar, orange, bear, television, porcupine, fox, trout, snake, skyscraper, bus, rocket, pear, spider, ray, sweet_pepper, baby, poppy, caterpillar, chimpanzee, maple_tree, sea, beaver, aquarium_fish, couch, road, plate, tiger, wolf, hamster, camel