Hinge Loss Formula for Segment-Based Reward Model Training

A reward model is being trained to classify text segments as either 'appropriate' (target value +1) or 'inappropriate' (target value -1). The training uses a max-margin loss function, which aims to ensure that the model's output score for a segment is not only on the correct side of the decision boundary but also surpasses it by a certain margin. If the score meets or exceeds this margin, the loss is zero. Assuming the required margin is 1, in which of the following scenarios would the loss for

Analyzing Reward Model Penalties with Max-Margin Loss

Comparing Loss Function Behaviors in Reward Modeling