ankur310794
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README.md
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---
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tags:
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- generated_from_keras_callback
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model-index:
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- name: dpr-question_encoder_bert_uncased_L-12_H-128_A-2
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results: []
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# dpr-question_encoder_bert_uncased_L-12_H-128_A-2
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This model was trained from scratch on
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It achieves the following results on the evaluation set:
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##
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## Training procedure
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### Training hyperparameters
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- optimizer: None
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- training_precision: float32
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### Training results
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### Framework versions
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- Transformers 4.15.0
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- TensorFlow 2.7.0
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- Tokenizers 0.10.3
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---
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tags:
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- generated_from_keras_callback
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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-12_H-128_A-2
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results: []
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# dpr-question_encoder_bert_uncased_L-12_H-128_A-2
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This model(google/bert_uncased_L-12_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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## Evaluation data
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evaluation dataset: facebook-dpr-dev-dataset from official DPR github
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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-12_H-128_A-2(our)|nq-dev dataset|6445|199795|60.53%|68.28%|76.07%|80.98%|91.45%|
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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-12_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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### Training hyperparameters
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- optimizer: None
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- training_precision: float32
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### Framework versions
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- Transformers 4.15.0
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- TensorFlow 2.7.0
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- Tokenizers 0.10.3
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