I added few tokens to the tokenizer, and would like now to train roberta model. Will it automatically also tune the embedding layer (the layer that embeds the tokens), or is there any flag or anything else I should change so that embedding layer will be tuned? Schematically, my code looks like that:

model = RobertaForSequenceClassification.from_pretrained(‘roberta-base’, num_labels=2)
trainer = Trainer(
model=model,
args=training_args,  # training arguments, defined above
…
)
trainer.train()

and the input data is the tokenized data.