EXPLORING THE CAPABILITIES OF CHATGPT IN NATURAL LANGUAGE PROCESSING TASKS
Keywords:
ChatGPT, Natural Language Processing, Language Models, Hyperparameters, Low-resource Settings, Ethical ImplicationsAbstract
ChatGPT is a state-of-the-art language model developed by OpenAI that has demonstrated impressive capabilities in natural language processing (NLP) tasks such as text generation, sentiment analysis, and text classification. This paper aims to explore the capabilities of ChatGPT in NLP tasks by analyzing its language understanding and generation abilities, comparing its performance with other language models, and evaluating the impact of pretraining data and hyperparameters on its performance. We conducted experiments on multiple datasets and tasks, including sentiment analysis, text classification, and conversational agents, and found that ChatGPT outperforms most other language models in terms of language generation and is highly competitive in language understanding tasks. However, we also identified some limitations and challenges of ChatGPT, such as its tendency to generate biased or offensive language and its high computational and memory requirements. We discuss the implications of these findings and suggest strategies for improving the performance and ethical use of ChatGPT in NLP. Overall, our study provides insights into the strengths and weaknesses of ChatGPT and its potential for advancing the field of NLP.
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