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@ -30,12 +30,6 @@ logger = logging.getLogger(__name__)
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class Seq2SeqTrainingArguments(TrainingArguments):
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class Seq2SeqTrainingArguments(TrainingArguments):
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"""
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"""
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Args:
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Args:
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sortish_sampler (`bool`, *optional*, defaults to `False`):
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Whether to use a *sortish sampler* or not. Only possible if the underlying datasets are *Seq2SeqDataset*
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for now but will become generally available in the near future.
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It sorts the inputs according to lengths in order to minimize the padding size, with a bit of randomness
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for the training set.
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predict_with_generate (`bool`, *optional*, defaults to `False`):
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predict_with_generate (`bool`, *optional*, defaults to `False`):
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Whether to use generate to calculate generative metrics (ROUGE, BLEU).
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Whether to use generate to calculate generative metrics (ROUGE, BLEU).
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generation_max_length (`int`, *optional*):
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generation_max_length (`int`, *optional*):
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