[8] GPT2 - Language Models are Unsupervised Multitask Learners

Title: Language Models are Unsupervised Multitask Learners

Authors & Year: Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever, 2019

Link: https://cdn.openai.com/better-language-models/language_models_are_unsupervised_multitask_learners.pdf

Objective: Investigate the capabilities of large-scale unsupervised language models and demonstrate their potential for multitask learning. Context: Pre-training large unsupervised language models has gained popularity in NLP, but there is a need to understand their capabilities and limitations.

Key Contributions:

• Introduced GPT-2, a large-scale unsupervised language model based on the transformer architecture.

• Demonstrated the effectiveness of GPT-2 in various NLP tasks without task-specific training, showcasing the multitask learning potential of unsupervised language models.

Methodology:

• GPT-2 is a pre-trained, unidirectional transformer model that leverages unsupervised learning for pre-training.

• The model is trained on a large corpus of text using a causal language modeling objective.

• GPT-2 is evaluated on various NLP tasks, such as translation, summarization, and question-answering, without task-specific training.

Results:

• GPT-2 achieved strong performance on multiple NLP tasks without task-specific fine-tuning, indicating its multitask learning capabilities.

• The model demonstrated coherent text generation, even for long sequences, but also showed limitations in terms of factual correctness and potential biases.

Impact:

• GPT-2 highlighted the potential of large-scale unsupervised language models for multitask learning in NLP.

• The model raised concerns about the risks associated with deploying powerful language models and inspired discussions on AI safety and ethics.

Takeaways:

• GPT-2 is a large-scale unsupervised language model that demonstrates strong multitask learning capabilities across various NLP tasks without task-specific training.

• The model has made significant contributions to NLP research, showcasing the potential of unsupervised learning for multitask learning and raising awareness about AI safety and ethical concerns.

• GPT-2 has paved the way for the development of more advanced language models, such as GPT-3.