Preparing Practice Exam…
Please wait a moment while the system generates the exam questions, answers, and study session.
Please wait a moment while the system generates the exam questions, answers, and study session.
AWS Certified AI Practitioner · AWS
Select one answer.
Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.
C is the correct answer
A Pontuação F1 é uma métrica essencial para avaliar modelos de linguagem, pois considera precisão e recall. Ela mede o equilíbrio entre respostas corretas e a capacidade do modelo de recuperar informações relevantes. Aqui está um resumo das outras opções: Precisão mede a taxa de respostas corretas, mas não considera se o modelo deixa de recuperar informações importantes. Tempo para o primeiro token avalia a rapidez da resposta, mas não a qualidade. Taxa de erro de palavras é usada mais para reconhecimento de voz e não é ideal para medir a eficácia de um chatbot de help desk.
The F1 score is a widely used metric for evaluating the accuracy of a model, especially in classification tasks where there is an imbalance between precision and recall. It is the harmonic mean of precision and recall, providing a balanced measure of the model’s ability to correctly identify relevant information while minimizing false positives and false negatives. In the context of a help desk model, you want to measure both the precision (correctness of answers) and recall (how well the model retrieves the relevant information). The F1 score helps you achieve a balanced view of these two metrics, making it a good choice for evaluating model accuracy in a fine-tuned large language model (LLM) for answering questions.