remove useless and confusing lm_labels line (#3531)

src/transformers/modeling_t5.py

@@ -901,7 +901,6 @@ class T5ForConditionalGeneration(T5PreTrainedModel):
         lm_labels (:obj:`torch.LongTensor` of shape :obj:`(batch_size,)`, `optional`, defaults to :obj:`None`):
                 Labels for computing the sequence classification/regression loss.
                 Indices should be in :obj:`[-100, 0, ..., config.vocab_size - 1]`.
-                If :obj:`config.num_labels > 1` a classification loss is computed (Cross-Entropy).
                 All labels set to ``-100`` are ignored (masked), the loss is only
                 computed for labels in ``[0, ..., config.vocab_size]``