Save model to disk after training about setfit HOT 2 CLOSED

# Create trainer
trainer = SetFitTrainer(
    model=model,
    train_dataset=train_dataset,
    eval_dataset=eval_dataset,
    loss_class=CosineSimilarityLoss,
    batch_size=16,
    num_iterations=20, # The number of text pairs to generate for contrastive learning
    column_mapping={"sentence": "text", "label": "label"} # Map dataset columns to text/label expected by trainer
)

# Train and evaluate
trainer.train()
metrics = trainer.evaluate()

save_directory = "/path/to/local/dir"
trainer.model._save_pretrained(save_directory=save_directory)