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This project is aimed at developing a machine translation system for translating Urdu text into English using the Transformer-based architecture.

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Kheem-Dh/Urdu-to-English-Machine-Translation-using-Seq2Seq-Transformers-Variant-Model

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Urdu-to-English-Machine-Translation-using-Seq2Seq-Transformers-Variant-Model

This project is aimed at developing a machine translation system for translating Urdu text into English using the Transformer-based architecture. The Transformer-based architecture is a deep learning-based approach that uses self-attention mechanisms to learn the contextual relationship between words in a sentence. The model consists of multiple layers of encoders and decoders, and is trained on a large dataset of parallel Urdu-English sentences. The model is designed to capture the nuances of the source language, while producing accurate and fluent translations in the target language. The system is evaluated with a combination of automatic metrics and human judgement, and can be used for various applications such as language learning, information retrieval, and natural language processing.

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This project is aimed at developing a machine translation system for translating Urdu text into English using the Transformer-based architecture.

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