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--- |
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language: multilingual |
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datasets: |
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- NQ |
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- Trivia |
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- SQuAD |
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- MLQA |
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- DRCD |
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--- |
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# dpr-ctx_encoder-bert-base-multilingual |
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## Description |
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Multilingual DPR Model base on bert-base-multilingual-cased. |
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[DPR model](https://arxiv.org/abs/2004.04906) |
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[DPR repo](https://github.com/facebookresearch/DPR) |
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## Data |
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1. [NQ](https://github.com/facebookresearch/DPR/blob/master/data/download_data.py) |
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2. [Trivia](https://github.com/facebookresearch/DPR/blob/master/data/download_data.py) |
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3. [SQuAD](https://github.com/facebookresearch/DPR/blob/master/data/download_data.py) |
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4. [DRCD*](https://github.com/DRCKnowledgeTeam/DRCD) |
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5. [MLQA*](https://github.com/facebookresearch/MLQA) |
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`question pairs for train`： 644,217 |
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`question pairs for dev`： 73,710 |
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*DRCD and MLQA are converted using script from haystack [squad_to_dpr.py](https://github.com/deepset-ai/haystack/blob/master/haystack/retriever/squad_to_dpr.py) |
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## Training Script |
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I use the script from [haystack](https://colab.research.google.com/github/deepset-ai/haystack/blob/master/tutorials/Tutorial9_DPR_training.ipynb) |
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## Usage |
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```python |
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from transformers import DPRQuestionEncoder, DPRQuestionEncoderTokenizer |
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tokenizer = DPRQuestionEncoderTokenizer.from_pretrained('voidful/dpr-question_encoder-bert-base-multilingual') |
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model = DPRQuestionEncoder.from_pretrained('voidful/dpr-question_encoder-bert-base-multilingual') |
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input_ids = tokenizer("Hello, is my dog cute ?", return_tensors='pt')["input_ids"] |
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embeddings = model(input_ids).pooler_output |
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``` |
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Follow the tutorial from `haystack`: |
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[Better Retrievers via "Dense Passage Retrieval"](https://colab.research.google.com/github/deepset-ai/haystack/blob/master/tutorials/Tutorial6_Better_Retrieval_via_DPR.ipynb) |
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``` |
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from haystack.retriever.dense import DensePassageRetriever |
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retriever = DensePassageRetriever(document_store=document_store, |
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query_embedding_model="voidful/dpr-question_encoder-bert-base-multilingual", |
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passage_embedding_model="voidful/dpr-ctx_encoder-bert-base-multilingual", |
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max_seq_len_query=64, |
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max_seq_len_passage=256, |
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batch_size=16, |
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use_gpu=True, |
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embed_title=True, |
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use_fast_tokenizers=True) |
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``` |
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