Model isn't saved on "save_steps" 
I am trying to train a T5 model on Colab Using examples, I run the following code:

```
!python run_t5_mlm_flax.py \
	--output_dir="/content/drive/MyDrive/Pouramini/" \
	--model_type="t5" \
	--config_name="/content/drive/MyDrive/Pouramini/" \
	--tokenizer_name="/content/drive/MyDrive/Pouramini/" \
	--dataset_name="oscar" \
	--dataset_config_name="unshuffled_deduplicated_fa" \
	--max_seq_length="512" \
	--per_device_train_batch_size="64" \
	--per_device_eval_batch_size="64" \
	--adafactor \
	--learning_rate="0.005" \
	--weight_decay="0.001" \
	--warmup_steps="2000" \
	--overwrite_output_dir \
	--logging_steps="500" \
	--save_steps="100" \
	--eval_steps="100"
```
Since I want to be able to resume the model train, I set `save_steps` on 100. However, while the progress bar shows step 
```
  7% 510/7794 [1:11:36<24:59:20, 12.35s/ba]
```
There is nothing in my `output_directory` except for config and tokenizer json files, which existed before training.
I also set  `--max_steps="150"  ` to see if it saves the model after 150 steps, but nothing happened and it's still running in step 300!!<|||||>Thank you for reporting this! I will take a look.<|||||>@patil-suraj  Okay, it's now training. In fact, it was in pre-processing stages for dataset and I though it's training. Now it saves the model on "save_steps".

