Я хочу обучить модель vad из pynnote.audio на своих данных, но сейчас у меня падает ошибка
{
	"name": "ValueError",
	"message": "Caught ValueError in DataLoader worker process 0.
Original Traceback (most recent call last):
  File \"/home/ubuntu/.local/lib/python3.10/site-packages/torch/utils/data/_utils/worker.py\", line 308, in _worker_loop
    data = fetcher.fetch(index)  # type: ignore[possibly-undefined]
  File \"/home/ubuntu/.local/lib/python3.10/site-packages/torch/utils/data/_utils/fetch.py\", line 51, in fetch
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File \"/home/ubuntu/.local/lib/python3.10/site-packages/torch/utils/data/_utils/fetch.py\", line 51, in <listcomp>
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File \"/home/ubuntu/.local/lib/python3.10/site-packages/pyannote/audio/core/task.py\", line 148, in __getitem__
    return self.task.val__getitem__(idx)
  File \"/home/ubuntu/.local/lib/python3.10/site-packages/pyannote/audio/tasks/segmentation/mixins.py\", line 565, in val__getitem__
    return self.prepare_chunk(
  File \"/home/ubuntu/.local/lib/python3.10/site-packages/pyannote/audio/tasks/segmentation/voice_activity_detection.py\", line 145, in prepare_chunk
    sample[\"X\"], _ = self.model.audio.crop(file, chunk, duration=duration)
  File \"/home/ubuntu/.local/lib/python3.10/site-packages/pyannote/audio/core/io.py\", line 371, in crop
    raise ValueError(
ValueError: requested fixed duration (2.000000s, or 48000 frames) is longer than file duration (0.029375s, or 705 frames).
",
	"stack": "---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[8], line 5
      1 import pytorch_lightning as pl
      3 trainer = pl.Trainer(devices=1, max_epochs=1)
----> 5 trainer.fit(model)

File ~/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py:544, in Trainer.fit(self, model, train_dataloaders, val_dataloaders, datamodule, ckpt_path)
    542 self.state.status = TrainerStatus.RUNNING
    543 self.training = True
--> 544 call._call_and_handle_interrupt(
    545     self, self._fit_impl, model, train_dataloaders, val_dataloaders, datamodule, ckpt_path
    546 )

File ~/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/call.py:44, in _call_and_handle_interrupt(trainer, trainer_fn, *args, **kwargs)
     42     if trainer.strategy.launcher is not None:
     43         return trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer, **kwargs)
---> 44     return trainer_fn(*args, **kwargs)
     46 except _TunerExitException:
     47     _call_teardown_hook(trainer)

File ~/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py:580, in Trainer._fit_impl(self, model, train_dataloaders, val_dataloaders, datamodule, ckpt_path)
    573 assert self.state.fn is not None
    574 ckpt_path = self._checkpoint_connector._select_ckpt_path(
    575     self.state.fn,
    576     ckpt_path,
    577     model_provided=True,
    578     model_connected=self.lightning_module is not None,
    579 )
--> 580 self._run(model, ckpt_path=ckpt_path)
    582 assert self.state.stopped
    583 self.training = False

File ~/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py:987, in Trainer._run(self, model, ckpt_path)
    982 self._signal_connector.register_signal_handlers()
    984 # ----------------------------
    985 # RUN THE TRAINER
    986 # ----------------------------
--> 987 results = self._run_stage()
    989 # ----------------------------
    990 # POST-Training CLEAN UP
    991 # ----------------------------
    992 log.debug(f\"{self.__class__.__name__}: trainer tearing down\")

File ~/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py:1031, in Trainer._run_stage(self)
   1029 if self.training:
   1030     with isolate_rng():
-> 1031         self._run_sanity_check()
   1032     with torch.autograd.set_detect_anomaly(self._detect_anomaly):
   1033         self.fit_loop.run()

File ~/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py:1060, in Trainer._run_sanity_check(self)
   1057 call._call_callback_hooks(self, \"on_sanity_check_start\")
   1059 # run eval step
-> 1060 val_loop.run()
   1062 call._call_callback_hooks(self, \"on_sanity_check_end\")
   1064 # reset logger connector

File ~/.local/lib/python3.10/site-packages/pytorch_lightning/loops/utilities.py:182, in _no_grad_context.<locals>._decorator(self, *args, **kwargs)
    180     context_manager = torch.no_grad
    181 with context_manager():
--> 182     return loop_run(self, *args, **kwargs)

File ~/.local/lib/python3.10/site-packages/pytorch_lightning/loops/evaluation_loop.py:128, in _EvaluationLoop.run(self)
    126 else:
    127     dataloader_iter = None
--> 128     batch, batch_idx, dataloader_idx = next(data_fetcher)
    129 if previous_dataloader_idx != dataloader_idx:
    130     # the dataloader has changed, notify the logger connector
    131     self._store_dataloader_outputs()

File ~/.local/lib/python3.10/site-packages/pytorch_lightning/loops/fetchers.py:133, in _PrefetchDataFetcher.__next__(self)
    130         self.done = not self.batches
    131 elif not self.done:
    132     # this will run only when no pre-fetching was done.
--> 133     batch = super().__next__()
    134 else:
    135     # the iterator is empty
    136     raise StopIteration

File ~/.local/lib/python3.10/site-packages/pytorch_lightning/loops/fetchers.py:60, in _DataFetcher.__next__(self)
     58 self._start_profiler()
     59 try:
---> 60     batch = next(self.iterator)
     61 except StopIteration:
     62     self.done = True

File ~/.local/lib/python3.10/site-packages/pytorch_lightning/utilities/combined_loader.py:341, in CombinedLoader.__next__(self)
    339 def __next__(self) -> _ITERATOR_RETURN:
    340     assert self._iterator is not None
--> 341     out = next(self._iterator)
    342     if isinstance(self._iterator, _Sequential):
    343         return out

File ~/.local/lib/python3.10/site-packages/pytorch_lightning/utilities/combined_loader.py:142, in _Sequential.__next__(self)
    139             raise StopIteration
    141 try:
--> 142     out = next(self.iterators[0])
    143 except StopIteration:
    144     # try the next iterator
    145     self._use_next_iterator()

File ~/.local/lib/python3.10/site-packages/torch/utils/data/dataloader.py:631, in _BaseDataLoaderIter.__next__(self)
    628 if self._sampler_iter is None:
    629     # TODO(https://github.com/pytorch/pytorch/issues/76750)
    630     self._reset()  # type: ignore[call-arg]
--> 631 data = self._next_data()
    632 self._num_yielded += 1
    633 if self._dataset_kind == _DatasetKind.Iterable and \\
    634         self._IterableDataset_len_called is not None and \\
    635         self._num_yielded > self._IterableDataset_len_called:

File ~/.local/lib/python3.10/site-packages/torch/utils/data/dataloader.py:1346, in _MultiProcessingDataLoaderIter._next_data(self)
   1344 else:
   1345     del self._task_info[idx]
-> 1346     return self._process_data(data)

File ~/.local/lib/python3.10/site-packages/torch/utils/data/dataloader.py:1372, in _MultiProcessingDataLoaderIter._process_data(self, data)
   1370 self._try_put_index()
   1371 if isinstance(data, ExceptionWrapper):
-> 1372     data.reraise()
   1373 return data

File ~/.local/lib/python3.10/site-packages/torch/_utils.py:705, in ExceptionWrapper.reraise(self)
    701 except TypeError:
    702     # If the exception takes multiple arguments, don't try to
    703     # instantiate since we don't know how to
    704     raise RuntimeError(msg) from None
--> 705 raise exception

ValueError: Caught ValueError in DataLoader worker process 0.
Original Traceback (most recent call last):
  File \"/home/ubuntu/.local/lib/python3.10/site-packages/torch/utils/data/_utils/worker.py\", line 308, in _worker_loop
    data = fetcher.fetch(index)  # type: ignore[possibly-undefined]
  File \"/home/ubuntu/.local/lib/python3.10/site-packages/torch/utils/data/_utils/fetch.py\", line 51, in fetch
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File \"/home/ubuntu/.local/lib/python3.10/site-packages/torch/utils/data/_utils/fetch.py\", line 51, in <listcomp>
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File \"/home/ubuntu/.local/lib/python3.10/site-packages/pyannote/audio/core/task.py\", line 148, in __getitem__
    return self.task.val__getitem__(idx)
  File \"/home/ubuntu/.local/lib/python3.10/site-packages/pyannote/audio/tasks/segmentation/mixins.py\", line 565, in val__getitem__
    return self.prepare_chunk(
  File \"/home/ubuntu/.local/lib/python3.10/site-packages/pyannote/audio/tasks/segmentation/voice_activity_detection.py\", line 145, in prepare_chunk
    sample[\"X\"], _ = self.model.audio.crop(file, chunk, duration=duration)
  File \"/home/ubuntu/.local/lib/python3.10/site-packages/pyannote/audio/core/io.py\", line 371, in crop
    raise ValueError(
ValueError: requested fixed duration (2.000000s, or 48000 frames) is longer than file duration (0.029375s, or 705 frames).
"
}
В чем проблема и как ее исправить