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README.md
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We have trained a model to evaluate if a paraphrase is a semantic variation to the input query or just a surface level variation. Data augmentation by adding Surface level variations does not add much value to the NLP model training. if the approach to paraphrase generation is "OverGenerate and Rank" , Its important to have a robust model of scoring/ ranking paraphrases. NLG Metrics like bleu ,BleuRT, gleu , Meteor have not proved very effective in scoring paraphrases.
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```
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---
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license: apache-2.0
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inference: false
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We have trained a model to evaluate if a paraphrase is a semantic variation to the input query or just a surface level variation. Data augmentation by adding Surface level variations does not add much value to the NLP model training. if the approach to paraphrase generation is "OverGenerate and Rank" , Its important to have a robust model of scoring/ ranking paraphrases. NLG Metrics like bleu ,BleuRT, gleu , Meteor have not proved very effective in scoring paraphrases.
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```
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