ValueError: expected sequence of length 128 at dim 1 (got 68)
HI i am training a hf model “EleutherAI/pythia-70m” using hf dataset “lamini/lamini_docs” and but getting below error.the code is at kaggle notebook -FInetuning LLM | KaggleValueError                                Traceback (most recent call last)Cell In[193], line 1----> 1 training_output = trainer.train()File /opt/conda/lib/python3.10/site-packages/transformers/trainer.py:1591, in Trainer.train(self, resume_from_checkpoint, trial, ignore_keys_for_eval, **kwargs)1589         REDACTED_TOKEN_utils.enable_progress_bars()1590 else:→ 1591     return inner_training_loop(1592         args=args,1593         resume_from_checkpoint=resume_from_checkpoint,1594         trial=trial,1595         ignore_keys_for_eval=ignore_keys_for_eval,1596     )File /opt/conda/lib/python3.10/site-packages/transformers/trainer.py:1870, in Trainer._inner_training_loop(self, batch_size, args, resume_from_checkpoint, trial, ignore_keys_for_eval)1867     rng_to_sync = True1869 step = -1→ 1870 for step, inputs in enumerate(epoch_iterator):1871     total_batched_samples += 11872     if rng_to_sync:File /opt/conda/lib/python3.10/site-packages/accelerate/data_loader.py:384, in DataLoaderShard.iter(self)382 # We iterate one batch ahead to check when we are at the end383 try:→ 384     current_batch = next(dataloader_iter)385 except StopIteration:386     yieldFile /opt/conda/lib/python3.10/site-packages/torch/utils/data/dataloader.py:634, in _BaseDataLoaderIter.next(self)631 if self._sampler_iter is None:632     # TODO(Bug in dataloader iterator found by mypy · Issue #76750 · pytorch/pytorch · GitHub)633     self._reset()  # type: ignore[call-arg]→ 634 data = self._next_data()635 self._num_yielded += 1636 if self._dataset_kind == _DatasetKind.Iterable and637         self._IterableDataset_len_called is not None and638         self._num_yielded > self._IterableDataset_len_called:File /opt/conda/lib/python3.10/site-packages/torch/utils/data/dataloader.py:678, in _SingleProcessDataLoaderIter._next_data(self)676 def _next_data(self):677     index = self._next_index()  # may raise StopIteration→ 678     data = self._dataset_fetcher.fetch(index)  # may raise StopIteration679     if self._pin_memory:680         data = _utils.pin_memory.pin_memory(data, self._pin_memory_device)File /opt/conda/lib/python3.10/site-packages/torch/utils/data/_utils/fetch.py:54, in _MapDatasetFetcher.fetch(self, possibly_batched_index)52 else:53     data = self.dataset[possibly_batched_index]—> 54 return self.collate_fn(data)File /opt/conda/lib/python3.10/site-packages/transformers/data/data_collator.py:70, in default_data_collator(features, return_tensors)64 # In this function we’ll make the assumption that allfeaturesin the batch65 # have the same attributes.66 # So we will look at the first element as a proxy for what attributes exist67 # on the whole batch.69 if return_tensors == “pt”:—> 70     return torch_default_data_collator(features)71 elif return_tensors == “tf”:72     return tf_default_data_collator(features)File /opt/conda/lib/python3.10/site-packages/transformers/data/data_collator.py:136, in torch_default_data_collator(features)134             batch[k] = torch.tensor(np.stack([f[k] for f in features]))135         else:→ 136             batch[k] = torch.tensor([f[k] for f in features])138 return batchValueError: expected sequence of length 128 at dim 1 (got 68)i have tried updating all packages (datasets,transformers) still no solution