Improve mismatched sizes management when loading a pretrained model (#17257)

- Add --ignore_mismatched_sizes argument to classification examples

- Expand the error message when loading a model whose head dimensions are different from expected dimensions

examples/pytorch/token-classification/README.md

@@ -55,6 +55,8 @@ uses special features of those tokenizers. You can check if your favorite model
 [this table](https://huggingface.co/transformers/index.html#supported-frameworks), if it doesn't you can still use the old version
 of the script.
 
+> If your model classification head dimensions do not fit the number of labels in the dataset, you can specify `--ignore_mismatched_sizes` to adapt it.
+
 ## Old version of the script
 
 You can find the old version of the PyTorch script [here](https://github.com/huggingface/transformers/blob/main/examples/legacy/token-classification/run_ner.py).

examples/pytorch/token-classification/run_ner.py

@@ -87,6 +87,10 @@ class ModelArguments:
             )
         },
     )
+    ignore_mismatched_sizes: bool = field(
+        default=False,
+        metadata={"help": "Will enable to load a pretrained model whose head dimensions are different."},
+    )
 
 
 @dataclass
@@ -364,6 +368,7 @@ def main():
         cache_dir=model_args.cache_dir,
         revision=model_args.model_revision,
         use_auth_token=True if model_args.use_auth_token else None,
+        ignore_mismatched_sizes=model_args.ignore_mismatched_sizes,
     )
 
     # Tokenizer check: this script requires a fast tokenizer.

examples/pytorch/token-classification/run_ner_no_trainer.py

@@ -223,6 +223,11 @@ def parse_args():
         action="store_true",
         help="Whether to load in all available experiment trackers from the environment and use them for logging.",
     )
+    parser.add_argument(
+        "--ignore_mismatched_sizes",
+        action="store_true",
+        help="Whether or not to enable to load a pretrained model whose head dimensions are different.",
+    )
     args = parser.parse_args()
 
     # Sanity checks
@@ -383,6 +388,7 @@ def main():
             args.model_name_or_path,
             from_tf=bool(".ckpt" in args.model_name_or_path),
             config=config,
+            ignore_mismatched_sizes=args.ignore_mismatched_sizes,
         )
     else:
         logger.info("Training new model from scratch")