A language model is fine-tuned for a sentiment analysis task with three possible labels: 'positive', 'negative', and 'neutral'. When given a new sentence, the model produces the following output vector, where each value corresponds to the probability of the respective label in the given order: [0.15, 0.80, 0.05]. How should this output be interpreted to determine the final classification?

Evaluating Model Output for Polarity Classification

A language model fine-tuned for a three-class polarity classification task (positive, negative, neutral) produces an output vector for a new input. The sum of the values in this output vector must equal 1.0.