chunk_content: .train()
  
  Evaluate
  	
  Word error rate (WER) is a common metric for evaluating ASR models. Load the WER metric from 🤗 Evaluate:
  
  
  	Copied
  import evaluate
  
  metric = evaluate.load("wer")
  Write a loop to evaluate the model performance. Set the model to evaluation mode first, and write the loop with torch.cuda.amp.autocast() because int8 training requires autocasting. Then, pass a batch of examples to the model to evaluate. Get the decoded prediction