nlp-with-deeplearning
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README.md
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tags:
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- nmt
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- aihub
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---
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tags:
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- nmt
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- aihub
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---
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# ENKO-T5-SMALL-V0
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This model is for English to Korean Machine Translator, which is based on T5-small architecture, but trained from scratch.
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#### Code
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The training code is from my lecture([LLM을 위한 김기현의 NLP EXPRESS](https://fastcampus.co.kr/data_online_nlpexpress)), which is published on [FastCampus](https://fastcampus.co.kr/). You can check the training code in this github [repo](https://github.com/kh-kim/nlp-express-practice).
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#### Dataset
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The training dataset for this model is mainly from [AI-Hub](https://www.aihub.or.kr/). The dataset consists of 11M parallel samples.
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#### Tokenizer
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I use Byte-level BPE tokenizer for both source and target language. Since it covers both languages, tokenizer vocab size is 60k.
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#### Architecture
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The model architecture is based on T5-small, which is popular encoder-decoder model architecture. Please, note that this model is trained from-scratch, not fine-tuned.
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#### Evaluation
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I conducted the evaluation with 5 different test sets. Following figure shows BLEU scores on each test set.
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![](images/enko.png)
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![](images/avg.png)
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DEEPCL model is private version of this model, which is trained on much more data.
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#### Contact
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Kim Ki Hyun ([email protected])
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images/avg.png
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images/enko.png
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