```python
tf_train_set = tokenized_squad["train"].to_tf_dataset(
    columns=["attention_mask", "input_ids", "start_positions", "end_positions"],
    dummy_labels=True,
    shuffle=True,
    batch_size=16,
    collate_fn=data_collator,
)
tf_validation_set = tokenized_squad["validation"].to_tf_dataset(
    columns=["attention_mask", "input_ids", "start_positions", "end_positions"],
    dummy_labels=True,
    shuffle=False,
    batch_size=16,
    collate_fn=data_collator,
)
```
Set up an optimizer function, learning rate schedule, and some training hyperparameters:
```python
from transformers import create_optimizer
batch_size = 16
num_epochs = 2
total_train_steps = (len(tokenized_squad["train"]) // batch_size) * num_epochs
optimizer, schedule = create_optimizer(
    init_lr=2e-5,
    num_warmup_steps=0,
