chunk_content: dataset = dataset.map(
      lambda x: {"text_label": [classes[label] for label in x["label"]]},
      batched=True,
      num_proc=1,
  )
  
  dataset["train"][0]
  {"sentence": "Profit before taxes was EUR 4.0 mn , down from EUR 4.9 mn .", "label": 0, "text_label": "negative"}
  
  Preprocess dataset
  	
  Initialize a tokenizer, and create a function to pad and truncate the model_inputs and labels:
  
  
  	Copied
  tokenizer = AutoTokenizer.from_pretrained(model_name_or