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_0462")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0462")Quick Links
Model-J: DINO Model (model_idx_0462)
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 | train |
| Base Model | facebook/dino-vitb16 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 0.0001 |
| LR Scheduler | cosine |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 462 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9847 |
| Val Accuracy | 0.9213 |
| Test Accuracy | 0.9168 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
tractor, seal, woman, porcupine, lamp, road, otter, beaver, camel, skunk, worm, tank, maple_tree, dinosaur, couch, crocodile, orange, plate, cattle, sweet_pepper, cup, television, rose, chimpanzee, skyscraper, forest, whale, bed, ray, pear, bowl, bicycle, streetcar, shark, train, cockroach, sea, pine_tree, rabbit, orchid, spider, aquarium_fish, clock, trout, bottle, hamster, shrew, bee, leopard, caterpillar
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Model tree for ProbeX/Model-J__DINO__model_idx_0462
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_0462") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")