wehub-resource-sync
31 lines
1.5 KiB
Markdown
31 lines
1.5 KiB
Markdown
# Pointer Generator Network for Text Summarization
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This code is the Paddle v2.0 implementation of *[Get To The Point: Summarization with Pointer-Generator Networks](https://arxiv.org/abs/1704.04368)*.
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The code adapts and aligns with [a previous Pytorch implementation](https://github.com/atulkum/pointer_summarizer).
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To reach the state-of-the-art performance stated in the source paper, please use the default hyper-parameters listed in *config.py*.
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## Model performance (with pointer generation and coverage loss enabled)
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After training for 100k iterations with *batch_size=8*, the Paddle implementation achieves a ROUGE-1-f1 of 0.3980 (0.3907 by [a previous Pytorch implementation](https://github.com/atulkum/pointer_summarizer) and 0.3953 by [the source paper](https://arxiv.org/abs/1704.04368)).
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```
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ROUGE-1:
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rouge_1_f_score: 0.3980 with confidence interval (0.3959, 0.4002)
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rouge_1_recall: 0.4639 with confidence interval (0.4613, 0.4667)
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rouge_1_precision: 0.3707 with confidence interval (0.3683, 0.3732)
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ROUGE-2:
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rouge_2_f_score: 0.1726 with confidence interval (0.1704, 0.1749)
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rouge_2_recall: 0.2008 with confidence interval (0.1984, 0.2034)
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rouge_2_precision: 0.1615 with confidence interval (0.1593, 0.1638)
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ROUGE-l:
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rouge_l_f_score: 0.3617 with confidence interval (0.3597, 0.3640)
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rouge_l_recall: 0.4214 with confidence interval (0.4188, 0.4242)
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rouge_l_precision: 0.3371 with confidence interval (0.3348, 0.3396)
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```
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[detail in](https://github.com/PaddlePaddle/PaddleNLP/tree/release/2.8/examples/text_summarization/pointer_summarizer)
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