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[docs] Fix the prompt link to the training script (#3060)
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This automatic linking doesn't work in an .rst section
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tomaarsen authored Nov 15, 2024
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Expand Up @@ -96,7 +96,7 @@ Additionally, some research papers (`INSTRUCTOR <https://arxiv.org/abs/2212.0974
```eval_rst
See the following script as an example of how to train with prompts in practice:
* `training_nq_prompts.py <training_nq_prompts.py>`_: This script finetunes `mpnet-base <https://huggingface.co/microsoft/mpnet-base>`_ on 100k query-answer pairs from the `natural-questions <https://huggingface.co/datasets/sentence-transformers/natural-questions>`_ dataset using the :class:`~sentence_transformers.losses.CachedMultipleNegativesRankingLoss` loss. The model is evaluated during training using the :class:`~sentence_transformers.evaluation.NanoBEIREvaluator`.
* `training_nq_prompts.py <https://github.com/UKPLab/sentence-transformers/blob/master/examples/training/prompts/training_nq_prompts.py>`_: This script finetunes `mpnet-base <https://huggingface.co/microsoft/mpnet-base>`_ on 100k query-answer pairs from the `natural-questions <https://huggingface.co/datasets/sentence-transformers/natural-questions>`_ dataset using the :class:`~sentence_transformers.losses.CachedMultipleNegativesRankingLoss` loss. The model is evaluated during training using the :class:`~sentence_transformers.evaluation.NanoBEIREvaluator`.
This script has two variables that affect 1) whether prompts are used and 2) whether prompts are included in the pooling. I have finetuned both ``mpnet-base`` and ``bert-base-uncased`` under the various different settings, resulting in a 0.66% and 0.90% relative improvements on ``NDCG@10`` at no extra cost.
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