Update README.md

README.md

@@ -36,8 +36,7 @@ This is the model card of a 🤗 transformers model that has been pushed on the
 - **Input Format:** The model expects input in a text-to-text format. Specifically, you provide a prompt (e.g., the lecture content) and specify the desired task (e.g., “summarize”). The model then generates a summary as the output.
 - **Fine-Tuning:** The Lucas-Hyun-Lee/T5_small_lecture_summarization model has likely undergone fine-tuning on lecture-specific data. During fine-tuning, it learns to optimize its parameters for summarization by minimizing a loss function.
 - **Model Size:** As the name suggests, this is a small-sized variant of T5. Smaller models are computationally efficient and suitable for scenarios where memory or processing power is limited.
-- **Performance:** The model’s performance depends on the quality and diversity of the training data, as well as the specific lecture content it encounters during fine-tuning.
--  It should be evaluated based on metrics such as ROUGE (Recall-Oriented Understudy for Gisting Evaluation) scores.
+- **Performance:** The model’s performance depends on the quality and diversity of the training data, as well as the specific lecture content it encounters during fine-tuning. It should be evaluated based on metrics such as ROUGE (Recall-Oriented Understudy for Gisting Evaluation) scores.
 
 ### Model Sources [optional]