chunk_content: s.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(train_dataloader)
      train_ppl = torch.exp(train_epoch_loss)
      print(f"{epoch=}: {train_ppl=} {train_epoch_loss=} {eval_ppl=} {eval_e