code: def main():
      train_csv_path = "train.csv"
      eval_csv_path = "eval.csv"
  
      train_dataset = load_dataset("go_emotions", split="train[0:1999]")
      eval_dataset = load_dataset(
          "go_emotions", split="validation[0:199]"
      )
  
      generate_csv(train_csv_path, train_dataset)
      generate_csv(eval_csv_path, eval_dataset)
  
      happy_tc = HappyTextClassification(
          model_type="BERT",
          model_name="bert-base-uncased",
          num_labels=28,
      )
  
      train_args = TCTrainArgs(
          learning_rate=1e-5,
          num_train_epochs=1,
          # fp16=True,
          # report_to = ('wandb'),
          # project_name = "happy-transformer-examples",
          # run_name = "text-classification",
          # deepspeed="ZERO-2"
      )
  
      happy_tc.train(
          train_csv_path, args=train_args, eval_filepath=eval_csv_path
      )
  
      happy_tc.save("finetuned-model/")
  
imports: from datasets import load_dataset
  import csv
  from happytransformer import HappyTextClassification, TCTrainArgs
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types