Model-J DINO
Collection
1002 items • Updated
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__DINO__model_idx_0669")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0669")Quick Links
Model-J: DINO Model (model_idx_0669)
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 | DINO |
| Split | test |
| Base Model | facebook/dino-vitb16 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 669 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 1.0000 |
| Val Accuracy | 0.9133 |
| Test Accuracy | 0.9128 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
telephone, turtle, bicycle, tractor, pear, tank, oak_tree, worm, plain, keyboard, raccoon, orchid, chair, leopard, rabbit, cloud, mushroom, squirrel, butterfly, poppy, man, couch, skyscraper, willow_tree, pine_tree, bear, shark, sea, ray, motorcycle, elephant, house, whale, palm_tree, possum, orange, mouse, cattle, tulip, dinosaur, seal, trout, snail, flatfish, forest, mountain, bed, lawn_mower, camel, road
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Model tree for ProbeX/Model-J__DINO__model_idx_0669
Base model
facebook/dino-vitb16
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__DINO__model_idx_0669") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")