Datasets

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.. note::
    The ``sentence_transformers.sentence_transformer.datasets`` classes have been deprecated, and only exist for compatibility with the `deprecated training <../../sentence_transformer/training_overview.html#deprecated-training>`_.

    * Instead of :class:`~sentence_transformers.sentence_transformer.datasets.SentenceLabelDataset`, you can now use ``BatchSamplers.GROUP_BY_LABEL`` to use the :class:`~sentence_transformers.sampler.GroupByLabelBatchSampler`, which constructs each batch by drawing K samples from each of P distinct labels, ensuring every batch has at least 2 labels with at least 2 samples each.
    * Instead of :class:`~sentence_transformers.sentence_transformer.datasets.NoDuplicatesDataLoader`, you can now use the ``BatchSamplers.NO_DUPLICATES`` to use the :class:`~sentence_transformers.sampler.NoDuplicatesBatchSampler`.

sentence_transformers.sentence_transformer.datasets contains classes to organize your training input examples.

ParallelSentencesDataset

ParallelSentencesDataset is used for multilingual training. For details, see multilingual training.

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.. autoclass:: sentence_transformers.sentence_transformer.datasets.ParallelSentencesDataset

SentenceLabelDataset

SentenceLabelDataset can be used if you have labeled sentences and want to train with triplet loss.

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.. autoclass:: sentence_transformers.sentence_transformer.datasets.SentenceLabelDataset

DenoisingAutoEncoderDataset

DenoisingAutoEncoderDataset is used for unsupervised training with the TSDAE method.

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.. autoclass:: sentence_transformers.sentence_transformer.datasets.DenoisingAutoEncoderDataset

NoDuplicatesDataLoader

NoDuplicatesDataLoadercan be used together with MultipleNegativeRankingLoss to ensure that no duplicates are within the same batch.

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.. autoclass:: sentence_transformers.sentence_transformer.datasets.NoDuplicatesDataLoader