Update the doc string for T5WithLMHeadModel

T5WithLMHeadModel's doc string claims that indices of -1 are
ignored while computing the cross-entropy loss in the forward
pass; however, indices of -1 throw an error while indices of -100
are ignored. This commit updates the doc string to be consistent
with the class's behavior.

src/transformers/modeling_t5.py

@@ -802,9 +802,9 @@ class T5WithLMHeadModel(T5PreTrainedModel):
     r"""
         **lm_labels**: (`optional`) ``torch.LongTensor`` of shape ``(batch_size, sequence_length)``:
             Labels for computing the masked language modeling loss.
-            Indices should be in ``[-1, 0, ..., config.vocab_size]`` (see ``input_ids`` docstring)
-            Tokens with indices set to ``-1`` are ignored (masked), the loss is only computed for the tokens with labels
-            in ``[0, ..., config.vocab_size]``
+            Indices should either be in ``[0, ..., config.vocab_size]`` or -100 (see ``input_ids`` docstring).
+            Tokens with indices set to ``-100`` are ignored (masked), the loss is only computed for the tokens with labels
+            in ``[0, ..., config.vocab_size]``.
 
     Outputs: `Tuple` comprising various elements depending on the configuration (config) and inputs:
         **loss**: (`optional`, returned when ``lm_labels`` is provided) ``torch.FloatTensor`` of shape ``(1,)``: