Fine-tuning takes a pre-trained model and continues training it on your specific dataset — adapting its capabilities to your exact use case with relatively little data.

Why Fine-Tune?

• Dramatically better performance on domain-specific tasks
• Much less data and compute than training from scratch
• Consistent output format and style

The Trainer API

from transformers import Trainer, TrainingArguments

training_args = TrainingArguments(
    output_dir="./results",
    num_train_epochs=3,
    per_device_train_batch_size=16,
    evaluation_strategy="epoch",
)

trainer = Trainer(
    model=model,
    args=training_args,
    train_dataset=train_dataset,
    eval_dataset=eval_dataset,
)
trainer.train()

Reference:

Fine-tuning tutorial

https://huggingface.co/docs/transformers/training