Trainer multi label (#7191)

* Trainer accep multiple labels

* Missing import

* Fix dosctrings

src/transformers/training_args.py

@@ -2,7 +2,7 @@ import dataclasses
 import json
 import os
 from dataclasses import dataclass, field
-from typing import Any, Dict, Optional, Tuple
+from typing import Any, Dict, List, Optional, Tuple
 
 from .file_utils import cached_property, is_torch_available, is_torch_tpu_available, torch_required
 from .utils import logging
@@ -128,6 +128,12 @@ class TrainingArguments:
             forward method.
 
             (Note: this behavior is not implemented for :class:`~transformers.TFTrainer` yet.)
+        label_names (:obj:`List[str]`, `optional`):
+            The list of keys in your dictionary of inputs that correspond to the labels.
+
+            Will eventually default to :obj:`["labels"]` except if the model used is one of the
+            :obj:`XxxForQuestionAnswering` in which case it will default to
+            :obj:`["start_positions", "end_positions"]`.
     """
 
     output_dir: str = field(
@@ -253,13 +259,16 @@ class TrainingArguments:
         default=None, metadata={"help": "Whether or not to disable the tqdm progress bars."}
     )
 
-    def __post_init__(self):
-        if self.disable_tqdm is None:
-            self.disable_tqdm = logger.getEffectiveLevel() > logging.WARN
-
     remove_unused_columns: Optional[bool] = field(
         default=True, metadata={"help": "Remove columns not required by the model when using an nlp.Dataset."}
     )
+    label_names: Optional[List[str]] = field(
+        default=None, metadata={"help": "The list of keys in your dictionary of inputs that correspond to the labels."}
+    )
+
+    def __post_init__(self):
+        if self.disable_tqdm is None:
+            self.disable_tqdm = logger.getEffectiveLevel() > logging.WARN
 
     @property
     def train_batch_size(self) -> int: