parrot_paraphraser_on_T5

模型介绍

Parrot is a paraphrase based utterance augmentation framework purpose built to accelerate training NLU models. A paraphrase framework is more than just a paraphrasing model. For more details on the library and usage please refer to the github page **Huggingface** lists 12 paraphrase models, **RapidAPI** lists 7 fremium and commercial paraphrasers like QuillBot, Rasa has discussed an experimental paraphraser for augmenting text data here, Sentence-transfomers offers a paraphrase mining utility and NLPAug offers word level augmentation with a PPDB (a multi-million paraphrase database). While these attempts at paraphrasing are great, there are still some gaps and paraphrasing is NOT yet a mainstream option for text augmentation in building NLU models....Parrot is a humble attempt to fill some of these gaps. **What is a good paraphrase?** Almost all conditioned text generation models are validated on 2 factors, (1) if the generated text conveys the same meaning as the original context (Adequacy) (2) if the text is fluent / grammatically correct english (Fluency). For instance Neural Machine Translation outputs are tested for Adequacy and Fluency. But a good paraphrase should be adequate and fluent while being as different as possible on the surface lexical form. With respect to this definition, the **3 key metrics** that measures the quality of paraphrases are: - **Adequacy** (Is the meaning preserved adequately?) - **Fluency** (Is the paraphrase fluent English?) - **Diversity (Lexical / Phrasal / Syntactical)** (How much has the paraphrase changed the original sentence?)

主要特点

特点摘要待依据来源补齐，不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

来源报价与费用分析

同一模型在不同渠道、地区和配置下可能采用不同价格。下表独立保留各渠道报价，不将渠道价格视为厂商官方统一价格。

公开评测与运行配置

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

常见问题

资料来源与可追溯记录

许可证：未声明，须核验模型卡。模型介绍与第三方评测均以原来源的具体版本和方法为准。