Hi @valhalla, thanks for your reply, but I am still puzzled.
If I run
python run_glue.py --model_name_or_path bert-base-cased 
                               --task_name CoLA
                               --do_train
                               --do_eval
                               --data_dir ./CoLA
                               --max_seq_length 128
                               --per_device_train_batch_size 32
                               --learning_rate 2e-5
                               --num_train_epochs 3.0
                               --output_dir output
                               --evaluation_strategy steps
                               --logging_steps 8
                               --eval_steps 2 

validation metrics (e.g. eval_mcc, eval_loss) do not appear in the stdout logs before the end of the run, whereas training losses are displayed (as expected) every 8 trainer steps. Is this intended behavior?
Shouldn’t eval metrics appear every eval_steps*per_device_train_batch_size (or something along these lines?