Consider a training process where a small model first selects a subset of data from a large, initial dataset. A much larger model is then trained exclusively on this selected subset. If the large model trains without errors but ultimately performs poorly on its intended task, which of the following is the most likely reason for the failure, based on the logic of this specific workflow?

A machine learning pipeline uses a small model to select high-quality data for training a larger model. Arrange the following steps of this process into the correct chronological order.

Troubleshooting a Two-Stage Training Pipeline