# Initialise parameters
dataset = preprocess_dataset('IMDB Dataset Very Small.csv')
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
model = BertForSequenceClassification.from_pretrained(
    'bert-base-uncased',
    num_labels=2)
optimizer = AdamW(model.parameters())

# Fine-tune model using class
fine_tuned_model = FineTuningPipeline(
    dataset = dataset,
    tokenizer = tokenizer,
    model = model,
    optimizer = optimizer,
    val_size = 0.1,
    epochs = 2,
    seed = 42
    )

# Make some predictions using the validation dataset
model.predict(model.val_dataloader)