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---
title: LN2 Computer Vision
emoji: 💻
colorFrom: pink
colorTo: indigo
sdk: gradio
sdk_version: 5.25.2
app_file: app.py
pinned: false
---
## 🐶 Zero-Shot Classification on Oxford-IIIT Pet Dataset
This model was evaluated on the **Oxford-IIIT Pet Dataset** in a zero-shot setting using Hugging Face's 🤗 `transformers` and `datasets` libraries.
### 🧪 Task: Zero-Shot Image Classification
In this task, the model was used without any fine-tuning to classify pet images into breed categories. Each class label was passed as a candidate for classification using natural language descriptions. The model selected the most likely label for each image based on its learned knowledge.
### ✅ Results
| Metric | Value |
|------------|---------|
| Accuracy | 88.00% |
| Precision | 87.68% |
| Recall | 88.00% |
> ⚠️ Note: These results are based on zero-shot inference and do not reflect fine-tuned performance.
### 🧠 Model Used
We used the pre-trained [`openai/clip-vit-base-patch32`](https://huggingface.co/openai/clip-vit-base-patch32) for zero-shot classification.