Cannot pass inputs as dictionary to Roberta

I have a roberta-base model to which I want to pass my inputs. Here is a code snippet:

    with tqdm(train_loader, unit="train_batch", desc='Train') as tqdm_train_loader:
        for step, batch in enumerate(tqdm_train_loader):
            inputs = batch.pop("inputs")
            labels = batch.pop("labels")
            inputs = collate(inputs) # collate inputs
            for k, v in inputs.items(): # send each tensor value to `device`
                inputs[k] =
            labels = # send labels to `device`
            batch_size = labels.size(0)
            with torch.cuda.amp.autocast(enabled=config.APEX):
                y_preds = model(inputs) # <--- problem is here
                loss = criterion(y_preds, labels) # get loss

In my model definition, in the forward() method I pass the input in this way:

outputs = self.model(**inputs)

I don’t know why this is causing trouble, other models work fine when passing the inputs this way.

This is the error:

    804             raise ValueError("You have to specify either input_ids or inputs_embeds")
--> 806         batch_size, seq_length = input_shape
    807         device = input_ids.device if input_ids is not None else inputs_embeds.device

ValueError: too many values to unpack (expected 2)

Any help is appreciated.