---
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.