Release v1.0.0 · huggingface/setfit

v1.0.0 Full SetFit Release

This release heavily refactors the SetFit trainer and introduces some much requested features, such as:

New Trainer, new TrainingArguments with many, many new arguments.
Configurable logging, automatic logging to Weights & Biases and Tensorboard if installed.
Evaluation during training, early stopping support to combat overfitting.
Checkpointing + loading the best model at the end.
SetFit for Aspect Based Sentiment Analysis in collaboration with Intel Labs.
Heavily improved automatic model card generation.
Extensive callbacks support based on transformers.
Full, extensive documentation: http://hf.co/docs/setfit
and more!

Preserve dataset features in sample_dataset by @grofte in #396
Allow other datasets in trainer.evaluate() by @grofte in #402
Normalize device to CPU when evaluating by @tomaarsen in #363
show_progress_bar as parameter on predict and predict_prob by @davidsbatista in #429
Refactor to introduce Trainer & TrainingArguments, add SetFit ABSA by @tomaarsen in #265
fix: make sampling more reproducible by @yahiaelgamal in #441
Allow setting batch size in SetFitModel.predict by @tomaarsen in #443
Save differentiable model head on CPU by @tomaarsen in #444
Allow 'device' on SetFitModel.from_pretrained() by @tomaarsen in #445
Add notebook to demonstrate how efficiently running SetFit with ONNX by @MosheWasserb in #435
Add "labels" to SetFitModel, store/load from configuration file by @tomaarsen in #447
Allow passing strings to model.predict by @tomaarsen in #448
Allow partial column mappings by @tomaarsen in #449
Allow normalize_embeddings with a differentiable head by @tomaarsen in #450
Heavily improve automatic model card generation by @tomaarsen in #452
Also pass metric_kwargs to custom metric callable by @tomaarsen in #456
Prepare v1.0.0 release - Trainer, TrainingArguments, SetFitABSA, logging, evaluation during training, callbacks, docs by @tomaarsen in #439

Full Changelog: v0.7.0...v1.0.0