This project demonstrates how to fine-tune a pre-trained ResNet18 model using PyTorch for binary classification. This model is adapted to identify images in two classes: Positive and Negative.
The model had over 99% accuracy in binary classification. It identified misclassified samples to further strengthen its capabilities.
To get started, clone the repository and install the required dependencies:
In Docker and JupyterLab
git clone https://github.com/lucianoscarpaci/ResNet18-Evaluation-PyTorch.gitThis project is licensed under the MIT License.