code: def parse_args():
      parser = argparse.ArgumentParser()
      parser.add_argument(
          "-st",
          "--size-train-dataset",
          help="Number of samples to use from training data set. If not specified, use complete dataset",
          type=int,
          required=False,
      )
      parser.add_argument(
          "-se",
          "--size-eval-dataset",
          help="Number of samples to use from evaluation data set. If not specified, use complete dataset",
          type=int,
          required=False,
      )
      parser.add_argument(
          "-f",
          "--freeze-base-model",
          help="Freeze parameters of base model during training",
          action="store_true",
          required=False,
      )
      parser.add_argument(
          "-lr",
          "--learning-rate",
          help="Learning rate",
          type=float,
          required=False,
      )
      parser.add_argument(
          "-e",
          "--num_train_epochs",
          help="Number of training epochs",
          type=int,
          required=False,
      )
      parser.add_argument(
          "-b",
          "--per_device_train_batch_size",
          help="Per device batch size",
          type=int,
          required=False,
      )
      parser.add_argument(
          "-opt",
          "--optim",
          help="Optimizer (one of: adamw_hf, adamw_torch, adamw_apex_fused, or adafactor",
          type=str,
          required=False,
      )
      parser.add_argument(
          "-wd",
          "--weight_decay",
          help="Weight decay for AdamW optimizer",
          type=float,
          required=False,
      )
      parser.add_argument(
          "-b1",
          "--adam_beta1",
          help="beta1 hyperparameter for AdamW optimizer",
          type=float,
          required=False,
      )
      parser.add_argument(
          "-b2",
          "--adam_beta2",
          help="beta2 hyperparameter for AdamW optimizer",
          type=float,
          required=False,
      )
      parser.add_argument(
          "-eps",
          "--adam_epsilon",
          help="epsilon hyperparameter for AdamW optimizer",
          type=float,
          required=False,
      )
      parser.add_argument(
          "-log",
          "--logfile",
          help="Log file name and path",
          type=str,
          required=False,
      )
      args = parser.parse_args()
      return vars(args)
  
file_path: orion/examples/huggingface/main.py
imports: import logging
  import os
  import argparse
  from copy import deepcopy
  import hydra
  import numpy
  import torch
  from datasets import load_dataset, load_metric
  from omegaconf import DictConfig
  from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, DataCollatorForSeq2Seq, Seq2SeqTrainer, Seq2SeqTrainingArguments, TrainerCallback
label_desc: Use image node_id 1 for calling a global function with example usage: parse_args() and returns: vars