Prepare v1.0.0 release - Trainer, TrainingArguments, SetFitABSA, logging, evaluation during training, callbacks, docs
#439
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Note: This commit involves three deprecations: the SetFitTrainer class (and DistilledSetFitTrainer), additional arguments to Trainer.train and the keep_body_frozen argument to Trainer.unfreeze. The first and last of these are 'graceful', i.e. old code will still work, but the Trainer.train changes are breaking in some situations. For example, e.g. um_epochs can no longer be passed to Trainer.train. The new 'deprecated' test files are identical to the old test files. The goal here is to test whether old behaviour is still possible. For the most part it is, with exception of using Trainer.train with extra arguments. As a result, I skipped two tests in test_deprecated_trainer.py. Also note that docstrings have yet to be updated!
…rate The reasoning is that with body_learning_rate, the tuple is for (training embedding phase, training classifier phase), which matches the tuples that you should give to num_epochs and batch_size.
Also add DeprecationWarning for DistillationSetFitTrainer
Co-authored-by: lewtun <[email protected]>
Co-authored-by: lewtun <[email protected]>
Also remove unused SetFitBaseModel and SKLearnWrapper
This was referenced Dec 5, 2023
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Hello!
See also #265 for more details
Pull Request overview
Trainerclass with logging, evaluation during training, callbacks, etc.TrainingArgumentsclassAbsaModel&AbsaTrainer, see also Implement SetFit for ABSA from Intel Labs tomaarsen/setfit#6