Topic modeling is a technique used to analyze and generate medical texts. In this article, we will delve into the concept of topic coherence scores and its significance in evaluating the quality of generated text. We will also discuss other evaluation metrics and their implications on the accuracy and originality of the generated answers.
Topic Coherence Scores
A coherence score is a measure used to assess how well the terms used in a topic relate to each other. A higher coherence score indicates better semantic similarity among the terms, while a lower score suggests less relevance between them. For our fine-tuned model, the average coherence score was calculated at 0.3336, which falls under moderate level of coherence. This implies that there is a reasonable degree of connectedness among the terms used to describe the answer.
Evaluation Metrics
In addition to coherence scores, several other evaluation metrics were analyzed to evaluate the quality of generated text. These included relevance, accuracy, originality, and logic. Relevance was measured by assessing if the generated text is relevant to the question. Accuracy was gauged by checking if the generated answer contains accurate information that can be verified through evidence or other means. Originality was evaluated by analyzing if the generated text creates new insights and avoids repeated information, while logic was assessed by evaluating if the conveyed idea adheres to coherent and logical reasoning.
Conclusion
In conclusion, topic modeling is an essential technique used in medical text generation. Topic coherence scores are a crucial aspect of evaluating the quality of generated texts. The coherence score of 0.3336 indicates a moderate level of semantic similarity among the terms used to describe the answer. Other evaluation metrics, such as relevance, accuracy, originality, and logic, also contribute to understanding the overall quality of the generated text. By analyzing these metrics, we can gain insights into the effectiveness of the fine-tuned model in generating accurate, relevant, and original medical texts.
