I ran:-
python -m torch.distributed.launch --nproc_per_node=${num_gpus} \
  run_glue.py \
  --model_name_or_path microsoft/deberta-v3-large \
  --task_name $TASK_NAME \
  --do_train \
  --do_eval \
  --evaluation_strategy steps \
  --max_seq_length 256 \
  --warmup_steps 50 \
  --per_device_train_batch_size ${batch_size} \
  --learning_rate 6e-6 \
  --num_train_epochs 2 \
  --output_dir $output_dir \
  --overwrite_output_dir \
  --logging_steps 1000 \
  --logging_dir $output_dir

in the commands you are suggesting, how do input which model I want to train?