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README.md
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- dpr
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license: apache-2.0
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model-index:
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- name: dpr-question_encoder_bert_uncased_L-
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results: []
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---
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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probably proofread and complete it, then remove this comment. -->
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# dpr-question_encoder_bert_uncased_L-
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This model(google/bert_uncased_L-
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It achieves the following results on the evaluation set:
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|model_name|data_name|num of queries|num of passages|R@10|R@20|R@50|R@100|R@100|
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|nlpconnect/dpr-ctx_encoder_bert_uncased_L-
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|*facebook/dpr-ctx_encoder-single-nq-base(hf/fb)|nq-dev dataset|6445|199795|40.94%|49.27%|59.05%|66.00%|82.00%|
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evaluation dataset: UKPLab/beir test data but we have used first 2lac passage only.
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|model_name|data_name|num of queries|num of passages|R@10|R@20|R@50|R@100|R@100|
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|nlpconnect/dpr-ctx_encoder_bert_uncased_L-
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|*facebook/dpr-ctx_encoder-single-nq-base(hf/fb)|nq-test dataset|3452|200001|32.93%|43.74%|56.95%|66.30%|83.92%|
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Note: * means we have evaluated on same eval dataset.
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- dpr
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license: apache-2.0
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model-index:
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- name: dpr-question_encoder_bert_uncased_L-2_H-128_A-2
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results: []
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---
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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probably proofread and complete it, then remove this comment. -->
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# dpr-question_encoder_bert_uncased_L-2_H-128_A-2
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This model(google/bert_uncased_L-2_H-128_A-2) was trained from scratch on training data: data.retriever.nq-adv-hn-train(facebookresearch/DPR).
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It achieves the following results on the evaluation set:
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|model_name|data_name|num of queries|num of passages|R@10|R@20|R@50|R@100|R@100|
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|nlpconnect/dpr-ctx_encoder_bert_uncased_L-2_H-128_A-2(our)|nq-dev dataset|6445|199795|60.53%|68.28%|76.07%|80.98%|91.45%|
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|nlpconnect/dpr-ctx_encoder_bert_uncased_L-12_H-128_A-2(our)|nq-dev dataset|6445|199795|65.43%|71.99%|79.03%|83.24%|92.11%|
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|*facebook/dpr-ctx_encoder-single-nq-base(hf/fb)|nq-dev dataset|6445|199795|40.94%|49.27%|59.05%|66.00%|82.00%|
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evaluation dataset: UKPLab/beir test data but we have used first 2lac passage only.
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|model_name|data_name|num of queries|num of passages|R@10|R@20|R@50|R@100|R@100|
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|nlpconnect/dpr-ctx_encoder_bert_uncased_L-2_H-128_A-2(our)|nq-test dataset|3452|200001|49.68%|59.06%|69.40%|75.75%|89.28%|
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|*facebook/dpr-ctx_encoder-single-nq-base(hf/fb)|nq-test dataset|3452|200001|32.93%|43.74%|56.95%|66.30%|83.92%|
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Note: * means we have evaluated on same eval dataset.
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