Evaluating Abstractive Summarization (Chunk 5)
Evaluating using BERTScore
ROUGE relies on the exact presence of words in both the predicted and reference texts, failing to interpret the underlying semantics. This is where BERTScore comes in and leverages the contextual embeddings from the BERT model, aiming to evaluate the similarity between a predicted and a reference sentence in the context of machine-generated text. By comparing embeddings from both sentences, BERTScore captures semantic similarities that might be missed by traditional n-gram based metrics.