How to add evaluation?

I want to train the [vicuna-7b-v1.5] model with the following command:

deepspeed fastchat/train/train_lora.py \
--model_name_or_path lmsys/vicuna-7b-v1.5 \
--lora_r 32 \
--lora_alpha 64 \
--lora_dropout 0.05 \
--data_path ./data/etraindata.json \
--evaluation_data_file ./data/eevaldata.json \
--output_dir ./checkpointsbatch8grad24 \
--num_train_epochs 3 \
--fp16 True \
--per_device_train_batch_size 8 \
--per_device_eval_batch_size 8 \
--gradient_accumulation_steps 16 \
--evaluation_strategy "steps" \
--eval_steps 200 \
--save_strategy "steps" \
--save_steps 200 \
--save_total_limit 2 \
--learning_rate 2e-4 \
--weight_decay 0. \
--warmup_ratio 0.03 \
--lr_scheduler_type "cosine" \
--logging_strategy "steps" \
--logging_steps 1 \
--tf32 True \
--model_max_length 2048 \
--q_lora False \
--deepspeed playground/deepspeed_config_s2.json \
--gradient_checkpointing True \
--flash_attn False \
--report_to wandb \
--run_name "uWu"

but I am getting error as "evaluation_data_file is not recognized by HfArgumentParser"
How can I achieve this?
Also, how to get validation loss?

Start with train/train_lora.py and inspect the arguments passed to HfArgumentParser, comparing them with the command's evaluation_data_file option. Run the training command with a supported evaluation configuration and verify that validation loss is produced; the issue is resolved when evaluation data and validation loss work without the parser error.