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
eval_rst
.. autoclass:: sentence_transformers.losses.BatchAllTripletLoss
BatchHardSoftMarginTripletLoss
eval_rst
.. autoclass:: sentence_transformers.losses.BatchHardSoftMarginTripletLoss
BatchHardTripletLoss
eval_rst
.. autoclass:: sentence_transformers.losses.BatchHardTripletLoss
BatchSemiHardTripletLoss
eval_rst
.. autoclass:: sentence_transformers.losses.BatchSemiHardTripletLoss
