...     init_cell_selection_weights_to_zero=True,
...     select_one_column=True,
...     allow_empty_column_selection=False,
...     temperature=0.0352513,
... )
model = TapasForQuestionAnswering.from_pretrained("google/tapas-base", config=config)
optimizer = AdamW(model.parameters(), lr=5e-5)
model.train()
for epoch in range(2):  # loop over the dataset multiple times
...     for batch in train_dataloader:
...         # get the inputs;
...         input_ids = batch["input_ids"]
...         attention_mask = batch["attention_mask"]
...         token_type_ids = batch["token_type_ids"]
...         labels = batch["labels"]
...         numeric_values = batch["numeric_values"]
...         numeric_values_scale = batch["numeric_values_scale"]
...         float_answer = batch["float_answer"]
...         # zero the parameter gradients
