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While the model is powerful, it does have some limitations:
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Accuracy: The summaries generated might not always capture all the key points accurately, especially for complex or nuanced texts.
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Bias: The model can inherit biases present in the training data, which might affect the quality and neutrality of the summaries.
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Context Understanding: It might struggle with understanding the full context of very long documents, leading to incomplete or misleading summaries.
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Language and Style: The model’s output might not always match the desired tone or style, requiring further editing.
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Data Dependency: Performance can vary depending on the quality and nature of the input data. It performs best on data similar to its training set (news articles)
