switch from training_args.bin training_args.json

[not-lain]

What does this PR do?

switch from training_args.bin to training_args.json and only capture the parameters that the user passed
I'm using the same approach we are using in huggingface_hub's PyTorchModelHubMixin to store as little parameters as possible.
a minimalistic approach to test this is pr

from transformers import TrainingArguments
args = TrainingArguments(output_dir="folder",eval_strategy="no") # or any other paramters
print(args.to_json_string())
# outputs
"""
{
  "output_dir": "folder",
  "eval_strategy": "no",
  "logging_dir": "folder\\runs\\Nov29_02-44-45_iphone-laptop"
}
"""
# logging_dir is a special parameter that is always captured and added to the training_args because we want to ensure consistency

# stores the parameters into a file
args.to_json_file("training_args.json")

# loads an instance using the class directly
args2  = TrainingArguments.from_json_file("training_args.json") 

using this approach, we ensure that we only store the parameters that the user-defined manually and not the ones that have default values or the ones inferred from the system (ie cpu, cuda, tpu ... ), leaving some room for flexibility.

in a sense the parameters are mutable, meaning the user can physically alter them.

Fixes #34612

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@muellerzr @SunMarc