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## Evaluation results
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Each of the datasets' documents was summarized through every summarization method applied in the code and evaluated
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in comparison with the gold-standard summaries.
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Table
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| NN | 0.8269 | 0.8754 |0.7950 | 0.9773 |
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| DNN | 0.8462 | 0.8776 |0.8474 | 0.9123 |
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| CNN | 0.8462 | 0.8776 |0.8474 | 0.9123 |
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| LSTM | 0.8269 | 0.8801 |0.8571 | 0.9091 |
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## Checkpoints
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- Examples
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## Evaluation results
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Each of the datasets' documents was summarized through every summarization method applied in the code and evaluated
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in comparison with the gold-standard summaries. The following tables provide the results for many evaluation methods applied
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to the many datasets:
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Table 1: Scientific Papers (arXiv + PubMed) results
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![arxiv1](hhttps://huggingface.co/unb-lamfo-nlp-mcti/NLP-ATS-MCTI/resolve/main/tabela-arxiv-1.png)
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![arxiv2](hhttps://huggingface.co/unb-lamfo-nlp-mcti/NLP-ATS-MCTI/resolve/main/tabela-arxiv-2.png)
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Table 2: BIGPATENT results
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![bigpatent1](hhttps://huggingface.co/unb-lamfo-nlp-mcti/NLP-ATS-MCTI/resolve/main/tabela-bigpatent-1.png)
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![bigpatent2](hhttps://huggingface.co/unb-lamfo-nlp-mcti/NLP-ATS-MCTI/resolve/main/tabela-bigpatent-2.png)
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Table 3: CNN Corpus results
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![cnncorpus1](hhttps://huggingface.co/unb-lamfo-nlp-mcti/NLP-ATS-MCTI/resolve/main/tabela-cnncorpus-2.png)
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![cnncorpus2](hhttps://huggingface.co/unb-lamfo-nlp-mcti/NLP-ATS-MCTI/resolve/main/tabela-cnncorpus-2.png)
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Table 4: CNN + Daily Mail results
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![cnndm1](hhttps://huggingface.co/unb-lamfo-nlp-mcti/NLP-ATS-MCTI/resolve/main/tabela-cnn-dailymail-1.png)
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![cnndm2](hhttps://huggingface.co/unb-lamfo-nlp-mcti/NLP-ATS-MCTI/resolve/main/tabela-cnn-dailymail-2.png)
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Table 5: XSum results
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![xsum1](hhttps://huggingface.co/unb-lamfo-nlp-mcti/NLP-ATS-MCTI/resolve/main/tabela-xsum-1.png)
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![xsum2](hhttps://huggingface.co/unb-lamfo-nlp-mcti/NLP-ATS-MCTI/resolve/main/tabela-xsum-2.png)
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## Checkpoints
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- Examples
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