Model accuracy versus F1 When training a model (classifier) in TensorFlow, an accuracy value is returned. What is the interpretation of an accuracy of, say, 0.79. Furthermore, how does the accuracy relate to other evaluations of predictions, such as F1?

The accuracy is the proportion of correct predictions. To derive the F1 score, you need additional information drawn from the confusion matrix. The latter is easy to calculate with any classification model, see e.g., https://en.wikipedia.org/wiki/Confusion_matrix how to calculate a zillion statistics from it, including accuracy and F1 score.
