06f1fd69a6
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2.8 KiB
2.8 KiB
Trainer trainer
[Trainer] 클래스는 PyTorch에서 완전한 기능(feature-complete)의 훈련을 위한 API를 제공하며, 다중 GPU/TPU에서의 분산 훈련, NVIDIA GPU, AMD GPU를 위한 혼합 정밀도, 그리고 PyTorch의 torch.amp를 지원합니다. [Trainer]는 모델의 훈련 방식을 커스터마이즈할 수 있는 다양한 옵션을 제공하는 [TrainingArguments] 클래스와 함께 사용됩니다. 이 두 클래스는 함께 완전한 훈련 API를 제공합니다.
[Seq2SeqTrainer]와 [Seq2SeqTrainingArguments]는 [Trainer]와 [TrainingArguments] 클래스를 상속하며, 요약이나 번역과 같은 시퀀스-투-시퀀스 작업을 위한 모델 훈련에 적합하게 조정되어 있습니다.
[Trainer] 클래스는 🤗 Transformers 모델에 최적화되어 있으며, 다른 모델과 함께 사용될 때 예상치 못한 동작을 하게 될 수 있습니다. 자신만의 모델을 사용할 때는 다음을 확인하세요:
- 모델은 항상 튜플이나 [
~utils.ModelOutput]의 서브클래스를 반환해야 합니다. - 모델은
labels인자가 제공되면 손실을 계산할 수 있고, 모델이 튜플을 반환하는 경우 그 손실이 튜플의 첫 번째 요소로 반환되어야 합니다. - 모델은 여러 개의 레이블 인자를 수용할 수 있어야 하며, [
Trainer]에게 이름을 알리기 위해 [TrainingArguments]에서label_names를 사용하지만, 그 중 어느 것도"label"로 명명되어서는 안 됩니다.
Trainer transformers.Trainer
autodoc Trainer - all
Seq2SeqTrainer transformers.Seq2SeqTrainer
autodoc Seq2SeqTrainer - evaluate - predict
TrainingArguments transformers.TrainingArguments
autodoc TrainingArguments - all
Seq2SeqTrainingArguments transformers.Seq2SeqTrainingArguments
autodoc Seq2SeqTrainingArguments - all