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SenthilVikram Apr 1, 2021
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SenthilVikram Apr 2, 2021
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4 changes: 2 additions & 2 deletions README.md
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# PEGASUS library

Pre-training with Extracted Gap-sentences for Abstractive SUmmarization
Pre-training with Extracted Gap-sentences for Abstractive Summarization
Sequence-to-sequence models, or PEGASUS, uses self-supervised objective Gap
Sentences Generation (GSG) to train a transformer encoder-decoder model. The
paper can be found on [arXiv](https://arxiv.org/abs/1912.08777). ICML 2020 accepted.
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## Evaluation metrics.

Evaluation results can be found in `mode_dir`. Summarization metrics are automatically
Evaluation results can be found in `model_dir`. Summarization metrics are automatically
calculated for each evaluation point.

- [ROUGE](https://www.aclweb.org/anthology/W04-1013.pdf) is the main metric
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