text: import transformers
  
  from data import load_data
  from postprocessing import read_proposals_files
  from ranker import train_ranker
  
  
  # Config
  transformers.logging.set_verbosity_info()
  
  # Load data
  train, val, test = load_data()
  
  files = [
      "BART-base-submission-23.csv", 
      "BART-large-submission-21.csv",
      "pegasus-large-submission-30.csv",
      "t5-base-submission-40.csv",
      "t5-small-submission-36.csv",
  ]
  
  train["name_proposals"] = read_proposals_files([f"train_{file}" for file in files])
  val["name_proposals"] = read_proposals_files([f"val_{file}" for file in files])
  
  # Train ranker
  trainer, model, tokenizer, collator = train_ranker("distilbert-base-uncased", train, val, train_batch_size=32, gradient_accumulation_steps=2)
  