👉 Pad math, or PadTest, is a method used to evaluate the performance of machine learning models, especially in natural language processing tasks. It involves generating a set of augmented or "pad" examples from the training data and then using these examples to assess how well the model generalizes beyond its original dataset. The pad math involves creating additional training instances by inserting special tokens (often called padding tokens) into the input sequences, which are then used alongside the original data during training. By measuring how well the model can predict these pad examples, pad math provides a more robust estimate of its generalization ability, helping to identify potential overfitting and ensuring the model performs well on unseen data.
