chunk_content: in batch.items()}
          with torch.no_grad():
              outputs = model(**batch)
          loss = outputs.loss
          eval_loss += loss.detach().float()
          eval_preds.extend(
              tokenizer.batch_decode(torch.argmax(outputs.logits, -1).detach().cpu().numpy(), skip_special_tokens=True)
          )
  
      eval_epoch_loss = eval_loss / len(eval_dataloader)
      eval_ppl = torch.exp(eval_epoch_loss)
      train_epoch_loss = total_loss / len