No labels column for tokenized data

I’m tokenizing to fine-tune a custom dataset with the goal of code generation. My tokenized dataset has the following columns: ['text', 'input_ids', 'attention_mask', "token_type_ids"], however, post-processing to fine-tune my model implies I have a ['label'] or target column. Since that is not evident here, my backward() call in training keeps failing.

Can someone help me clarify if these features (label, target…) are task-dependent? And if so, how one would go about this in tokenization?