Wrong weight initialization for TF t5 model
## Environment info
      - `transformers` version: 4.9.2
      - Platform: Linux-4.15.0-142-generic-x86_64-with-glibc2.29
      - Python version: 3.8.10
      - PyTorch version (GPU?): not installed (NA)
      - Tensorflow version (GPU?): 2.5.0 (True)
      - Flax version (CPU?/GPU?/TPU?): 0.3.4 (gpu)
      - Jax version: 0.2.18
      - JaxLib version: 0.1.69
      - Using GPU in script?: Yes
      - Using distributed or parallel set-up in script?: yes

### Who can help
@patil-suraj 
@patrickvonplaten 
## Information

Model I am using: Pre-training T5-base

The problem arises when using:
* [ ] the official example scripts: (give details below)
* [X] my own modified scripts: (give details below): Added to run_mlm.py the t5 data collator and keras adafactor optimizer

The tasks I am working on is:
* [X] my own task or dataset: Pre-training T5 base with oscar dataset (as in FLAX example)

## Expected behavior
Before updating init weights to normal distribution (as in transformers/src/transformers/models/t5/modeling_flax_t5.py) loss stuck at 4.5 (unlike FLAX behaviour). after update of init weights i get same behaviour as in FLAX and reach <2 loss.

Example:
In flax code: class: FlaxT5DenseReluDense: lines 95:,96 
    wi_init_std = self.config.initializer_factor * (self.config.d_model ** -0.5)
    wo_init_std = self.config.initializer_factor * (self.config.d_ff ** -0.5)

In TF code, the default initializer is used. My suggested fix:
        wi_initializer = tf.keras.initializers.RandomNormal(mean = 0, stddev = config.initializer_factor * (config.d_model ** -0.5))
        wo_initializer = tf.keras.initializers.RandomNormal(mean = 0, stddev = config.initializer_factor * (config.d_ff ** -0.5))
        self.wi = tf.keras.layers.Dense(config.d_ff, use_bias=False, name="wi",kernel_initializer=wi_initializer)
        self.wo = tf.keras.layers.Dense(config.d_model, use_bias=False, name="wo",kernel_initializer=wo_initializer)

This is relevant for all weights and embeddings initialization.


I agree! Would you like to open a PR to fix it? :-)<|||||>Will try to do it on coming days<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.