Report the results in read.me

README.md

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-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+## 🐶 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.
+