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_0085)
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 |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 85 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8949 |
| Val Accuracy | 0.8435 |
| Test Accuracy | 0.8424 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
hamster, chair, lizard, couch, butterfly, wardrobe, mushroom, lion, snake, plain, shark, porcupine, bridge, mouse, kangaroo, sea, lobster, tulip, shrew, table, bear, spider, mountain, apple, cockroach, girl, flatfish, keyboard, dinosaur, bottle, poppy, wolf, rocket, crocodile, clock, castle, seal, bed, bee, pine_tree, forest, cattle, skyscraper, willow_tree, otter, fox, orchid, road, sunflower, tiger