GPT-3’s Performance on Standard NLP Tasks

NLP tasks

GPT-3 is a highly advanced and sophisticated successor to the NLP field, built and trained using the core NLP approaches and deep neural networks. For any AI-based modeling approach, the model performance is evaluated in the following way: First, we train the model for a specific task (like classification, Q/A, text generation, etc.) on training data; then, we verify the model performance using the test data (unseen data).

Similarly, there is a standard set of NLP benchmarks for evaluating the performance of NLP models and coming up with a relative model ranking or comparison. This comparison, or relative ranking, allows us to pick and choose the best model for a specific NLP task (business problem).

In this lesson, we will discuss the performance of GPT-3 on some standard NLP tasks, as seen in the illustration, and compare it with the performance of similar models on respective NLP tasks.