Wrong num_label configuration in Fine Tuning NER when model_name_or_path is specified
I have a pre-trained model that i have cached locally and i am passing model_name_or_path.

When i pass do_train, it results in the following code executing causing a second model reload. Unfortunately, this codepath ignores the config causing default num_labels to be passed leading to pytorch assert.

If last_checkpoint didn't detect it explicitly (at the beginning of main) wouldn't it be better to not reload unless explicitly asked by the user ?

 if last_checkpoint is not None:
            checkpoint = last_checkpoint
        elif os.path.isdir(model_args.model_name_or_path):
            checkpoint = model_args.model_name_or_path
        else:
            checkpoint = None
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