[Trainer.__init__]. So you may want to set this sooner (see the next example) if you tap into other
transformers functionality before creating the [Trainer] object.
Here is an example of how this can be used in an application:
```python
[...]
logger = logging.getLogger(name)
Setup logging
logging.basicConfig(
    format="%(asctime)s - %(levelname)s - %(name)s - %(message)s",
    datefmt="%m/%d/%Y %H:%M:%S",
    handlers=[logging.StreamHandler(sys.stdout)],
)
set the main code and the modules it uses to the same log-level according to the node
log_level = training_args.get_process_log_level()
logger.setLevel(log_level)
datasets.utils.logging.set_verbosity(log_level)
transformers.utils.logging.set_verbosity(log_level)
trainer = Trainer(...)
```
And then if you only want to see warnings on the main node and all other nodes to not print any most likely duplicated
