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Roberta: A Transformer based Approach for Semantic Address Matching Yassine Guermazi1, Sana Sellami1 and Omar Boucelma1 1Aix Marseille Univ, CNRS, IS, Marseille, FranceAbstractIn this paper, we describe
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A transformer-based approach is a method utilized primarily in natural language processing (NLP) tasks, employing transformer models to understand and generate human language.
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To fill out a transformer-based approach, one must provide detailed information about the model architecture, training data, intended applications, compliance with ethical guidelines, and expected outcomes.
The purpose of a transformer-based approach is to leverage the self-attention mechanism of transformer models to efficiently process and generate language, improving tasks such as translation, summarization, and conversation.
Information to be reported includes details about data sources, model parameters, performance metrics, potential biases, and safety considerations.
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