I start training my tuned in jupyter model with multiGPU with this script run_common_voice.py i see this error:

RuntimeError: Expected to mark a variable ready only once.
This error is caused by one of the following reasons: 1) Use of a module parameter outside the forward function. Please make sure model parameters are not shared across multiple concurrent forward-backward passes
2) Reused parameters in multiple reentrant backward passes. For example, if you use multiple checkpoint functions to wrap the same part of your model, it would result in the same set of parameters been used by different reentrant backward passes multiple times, and hence marking a variable ready multiple times. DDP does not support such use cases yet.

Traceback (most recent call last):
File “run_common_voice_rus.py”, line 434, in 
main()
File “run_common_voice_rus.py”, line 402, in main
train_result = trainer.train(resume_from_checkpoint=checkpoint)
File “/lib/python3.8/site-packages/transformers/trainer.py”, line 1056, in train
tr_loss += self.training_step(model, inputs)
File “run_common_voice_rus.py”, line 247, in training_step
self.scaler.scale(loss).backward()
File “/lib/python3.8/site-packages/torch/tensor.py”, line 245, in backward
torch.autograd.backward(self, gradient, retain_graph, create_graph, inputs=inputs)
File “/lib/python3.8/site-packages/torch/autograd/init.py”, line 145, in backward
Variable._execution_engine.run_backward(
File “/lib/python3.8/site-packages/torch/autograd/function.py”, line 89, in apply
return self._forward_cls.backward(self, *args)  # type: ignore
File “lib/python3.8/site-packages/torch/utils/checkpoint.py”, line 112, in backward
torch.autograd.backward(outputs_with_grad, args_with_grad)
File “/lib/python3.8/site-packages/torch/autograd/init.py”, line 145, in backward
Variable._execution_engine.run_backward(
@sgugger
What is the reason for this error? Why does it appear on the pre-train model?