Introduce warmup_ratio training argument
Author: tanmay17061
Pull request: yes

Introduce warmup_ratio training argument in both
TrainingArguments and TFTrainingArguments classes (#6673)

# What does this PR do?
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This PR will add a new argument `warmup_ratio` to both `TrainingArguments` and `TFTrainingArguments` classes. This can be used to specify the ratio of total training steps for which linear warmup will happen.  
This is especially convenient when the user wants to play around with the `num_train_epochs` or `max_steps` arguments while keeping the ratio of warmup steps a constant.
Fixes #6673


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Comments:
As per current implementation, any non-zero value given for `warmup_steps` will override any effects of `warmup_ratio`. It made sense for me to give higher precedence to `warmup_steps` as it seems to be the more inconvenient argument of the 2 to provide from user perspective. Please let me know if this default behaviour is to be changed.

PS: this is my first PR, so feel free to correct me. I will be happy to accommodate 😄 

Thanks for the review! I've incorporated the comments.  
Do let me know if anything else needs to be addressed.

Thanks for your comments!  
Agreed, the code looks much more readable now.  
Do let me know if there can be any more improvement.  

Thanks.

It would indeed be better in `TrainingArguments.__post_init__`: the rational for that is that when instantiating an object with wrong values, we want the error to be raised as soon as possible and as close as possible to the source for easy debugging.

In this case, the problem should appear at the line that parses the `TrainingArguments` or when they are created.

Thanks! Taken care of it.

Thanks for adding this functionality!