Day 20: Evaluating the accuracy of a VQA model

Today I created an evaluation function for my VQA model. Every loop over the data set I would print the average loss and the overall accuracy. Loss measure the incorrectness of a functions guess. Lower loss is good higher is bad. My function trended toward lower loss as it continued to train on the dataset. I was getting an accuracy of around 30% which is fairly good considering I was training the model on questions that had no associated images. In the future I plan to combine the image data with the question data.

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