Learn Before
A startup is developing a specialized chatbot for financial advice. To improve its performance, they implement the following data collection process: 1) They invite a group of beta testers to ask the chatbot any financial question they can think of. 2) They use their base language model to automatically generate an answer for each question. 3) They add these question-answer pairs directly to their fine-tuning dataset. What is the most significant weakness in this workflow that could compromise the quality of the final model?
0
1
Tags
Ch.4 Alignment - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Analysis in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
Related
Critique of a Data Sourcing Strategy
A team is building a dataset to improve a language model's ability to answer questions about a new software product. They plan to collect data from early users. Arrange the following stages into the correct sequence for their data collection and refinement process.
A startup is developing a specialized chatbot for financial advice. To improve its performance, they implement the following data collection process: 1) They invite a group of beta testers to ask the chatbot any financial question they can think of. 2) They use their base language model to automatically generate an answer for each question. 3) They add these question-answer pairs directly to their fine-tuning dataset. What is the most significant weakness in this workflow that could compromise the quality of the final model?