docs/package_reference/losses.md

Losses

sentence_transformers.losses define different loss functions, that can be used to fine-tune the network on training data. The loss function plays a critical role when fine-tuning the model. It determines how well our embedding model will work for the specific downstream task.

Sadly there is no "one size fits all" loss function. Which loss function is suitable depends on the available training data and on the target task.

BatchAllTripletLoss

.. autoclass:: sentence_transformers.losses.BatchAllTripletLoss

BatchHardSoftMarginTripletLoss

.. autoclass:: sentence_transformers.losses.BatchHardSoftMarginTripletLoss

BatchHardTripletLoss

.. autoclass:: sentence_transformers.losses.BatchHardTripletLoss

BatchSemiHardTripletLoss

.. autoclass:: sentence_transformers.losses.BatchSemiHardTripletLoss

ContrastiveLoss

.. autoclass:: sentence_transformers.losses.ContrastiveLoss

CosineSimilarityLoss

For each sentence pair, we pass sentence A and sentence B through our network which yields the embeddings u und v. The similarity of these embeddings is computed using cosine similarity and the result is compared to the gold similarity score.

This allows our network to be fine-tuned to recognize the similarity of sentences.

.. autoclass:: sentence_transformers.losses.CosineSimilarityLoss

DenoisingAutoEncoderLoss

.. autoclass:: sentence_transformers.losses.DenoisingAutoEncoderLoss

MarginMSELoss

.. autoclass:: sentence_transformers.losses.MarginMSELoss

MegaBatchMarginLoss

.. autoclass:: sentence_transformers.losses.MegaBatchMarginLoss

MSELoss

.. autoclass:: sentence_transformers.losses.MSELoss

MultipleNegativesRankingLoss

MultipleNegativesRankingLoss is a great loss function if you only have positive pairs, for example, only pairs of similar texts like pairs of paraphrases, pairs of duplicate questions, pairs of (query, response), or pairs of (source_language, target_language).

.. autoclass:: sentence_transformers.losses.MultipleNegativesRankingLoss

OnlineContrastiveLoss

.. autoclass:: sentence_transformers.losses.OnlineContrastiveLoss

SoftmaxLoss

.. autoclass:: sentence_transformers.losses.SoftmaxLoss

TripletLoss

.. autoclass:: sentence_transformers.losses.TripletLoss