Basically, despite providing the logging_steps argument, it doesn’t apparently override the default which I presume to be set to epoch - same with evaluation strategy which also runs during epochs instead of the no. of steps provided.
This is what the script receives on its side:-
adafactor=False,
adam_beta1=0.9,
adam_beta2=0.98,
adam_epsilon=1e-08,
dataloader_drop_last=False,
dataloader_num_workers=0,
dataloader_pin_memory=True,
ddp_find_unused_parameters=None,
debug=[],
deepspeed=None,
disable_tqdm=False,
do_eval=True,
do_predict=False,
do_train=True,
eval_accumulation_steps=10,
eval_steps=10,
evaluation_strategy=IntervalStrategy.STEPS,
fp16=False,
fp16_backend=auto,
fp16_full_eval=False,
fp16_opt_level=O1,
gradient_accumulation_steps=500,
greater_is_better=True,
group_by_length=False,
ignore_data_skip=False,
label_names=None,
label_smoothing_factor=0.0,
learning_rate=0.0003,
length_column_name=length,
load_best_model_at_end=True,
local_rank=-1,
log_level=20,
log_level_replica=-1,
log_on_each_node=True,
logging_dir=./logs,
logging_first_step=True,
logging_steps=10,
logging_strategy=IntervalStrategy.STEPS,
lr_scheduler_type=SchedulerType.LINEAR,
max_grad_norm=1.0,
max_steps=-1,
metric_for_best_model=accuracy,
mp_parameters=,
no_cuda=False,
num_train_epochs=1.0,
output_dir=./results,
overwrite_output_dir=True,
past_index=-1,
per_device_eval_batch_size=1,
per_device_train_batch_size=1,
prediction_loss_only=False,
push_to_hub=False,
push_to_hub_model_id=results,
push_to_hub_organization=None,
push_to_hub_token=None,
remove_unused_columns=True,
report_to=['tensorboard'],
resume_from_checkpoint=None,
run_name=./results,
save_on_each_node=False,
save_steps=500,
save_strategy=IntervalStrategy.EPOCH,
save_total_limit=None,
seed=42,
sharded_ddp=[],
skip_memory_metrics=False,
tpu_metrics_debug=False,
tpu_num_cores=8,
use_legacy_prediction_loop=False,
warmup_ratio=0.0,
warmup_steps=1000,
weight_decay=0.01,
)

Which seem to be true to my provided flags, but just not being acted upon.
Will dig more in the script to see what might be the issue.