A reward model is being trained to classify text segments. It uses the following loss function for a single segment, where a positive score indicates a desirable classification and a negative score indicates an undesirable one: Loss = max(0, 1 - (model_score * label)). The label is +1 for desirable segments and -1 for undesirable ones. If a segment with a ground-truth label of +1 receives a score of 0.3 from the model, what is the calculated loss for this segment?

Analyzing Reward Model Performance with Hinge Loss

Conditions for Zero Hinge Loss in a Reward Model