Evaluating an Image Classifier

This tutorial guides users through setting up an image classification experiment using Phoenix, a multi-modal evaluation and tracing platform. The process involves uploading a dataset, creating an experiment to classify the images, and evaluating the model's accuracy. OpenAI's GPT-4o-mini model is used for the classification task. Users are required to have an OpenAI API key ready and install necessary dependencies before connecting to Phoenix. The dataset is loaded from Hugging Face, converted to base64 encoded strings, and then uploaded to Phoenix. After defining the experiment task using OpenAI's GPT-4o-mini model, evaluators are set up to compare the model's output with the expected labels. Finally, the experiment is run, and users can modify their code and re-run the experiment for further evaluation.

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