text: import os
  import sys
  sys.path.append(os.getcwd())
  
  def autotrain(logfilepath,lr,batch_size,weight,epoch,modeldir):
  
     if modeldir.find('large') >= 0:
     #cmdline = "python3 oscar/run_objectid.py --learning_rate 1e-6 --model_name_or_path pretrained/pretrained_base/checkpoint-2000000  --do_train --do_eval  --evaluate_during_training  --data_dir data --learning_rate  "  + str(lr)  + "  --output_dir " + str(logfilepath) + "  --gradient_accumulation_steps "  + str(batch_size)  + "  --classoneweight " + str(weight)
          cmdline = "python3 oscar/run_objectid.py  --model_name_or_path pretrained/pretrained_large  --do_eval  --evaluate_during_training  --data_dir data --learning_rate  "  + str(lr)  + "  --output_dir " + str(logfilepath) + "  --gradient_accumulation_steps "  + str(batch_size)  + "  --classoneweight " + str(weight) + " --do_lower_case  --num_train_epochs "  + str(epoch) + " --eval_model_dir  " +  str(modeldir) 
     else:
          cmdline = "python3 oscar/run_objectid.py  --model_name_or_path pretrained/pretrained_base  --do_eval  --evaluate_during_training  --data_dir data --learning_rate  "  + str(lr)  + "  --output_dir " + str(logfilepath) + "  --gradient_accumulation_steps "  + str(batch_size)  + "  --classoneweight " + str(weight) + " --do_lower_case  --num_train_epochs "  + str(epoch) + " --eval_model_dir  " +  str(modeldir)
  
     print(cmdline)
     os.system(cmdline)
  #   cmdline = "python3 eval_new.py  " + logfilepath
  #   print(cmdline)
  #   os.system(cmdline)
  
  alldir = sys.argv[1]
  allfiles = os.listdir(alldir)
  modeldirs = []
  for filename in allfiles:
      if len(sys.argv) >= 3:
          ret = filename.find(sys.argv[2])
      else:
          ret = 1
   #   ret1 = filename.find('lowcase')
  
      if ret >=0:
           checkpointdirs = os.listdir(alldir + "/" + filename)
           for checkpointdir in checkpointdirs:
                ret1 = checkpointdir.find("checkpoint")
                if ret1 >= 0:
                   pytorchfiles =  os.listdir(alldir +  "/" + filename + "/" + checkpointdir)  
                   for pytorchfile in pytorchfiles:
                         if pytorchfile == 'pytorch_model.bin':
                            modeldirs.append( alldir + "/" + filename + "/" + checkpointdir) 
                 
  lr_list = []
  logfilepath = sys.argv[1] + 'test'
  for modeldir in modeldirs:
       autotrain(logfilepath,5e-5,1,3,1,modeldir)
  