Update README.md

README.md

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 This model is built to detect different types of skin cancer from dermatoscopic images. It was trained using the **HAM10000** dataset and is designed to classify seven types of skin lesions. The goal of this model is to assist in the early detection of skin cancer, particularly in regions where temperatures are rising, making skin cancer detection increasingly important.
 
 ## Model Overview
-The model is a Convolutional Neural Network (CNN) developed using **TensorFlow** and **Keras**. It takes input images of skin lesions and predicts one of the seven skin cancer classes. The model achieved an accuracy of **85%**, which can be further improved with fine-tuning and larger datasets.
+The model is a Convolutional Neural Network (CNN) developed using **TensorFlow** and **Keras**. It takes input images of skin lesions and predicts one of the seven skin cancer classes. The model achieved an accuracy of **73%**, which can be further improved with fine-tuning and larger datasets.
 
 ## Classes Detected
 The model predicts the following seven types of skin cancer: