from transformers import LayoutLMForTokenClassification, Trainer, TrainingArguments from datasets import load_dataset # Wczytanie przygotowanego zbioru danych dataset = load_dataset("json", data_files="training_data.json") # Ɓadowanie modelu LayoutLM do dostrajania model = LayoutLMForTokenClassification.from_pretrained("microsoft/layoutlmv3-base", num_labels=5) training_args = TrainingArguments( output_dir="./layoutlmv3_finetuned", per_device_train_batch_size=4, per_device_eval_batch_size=4, num_train_epochs=5, evaluation_strategy="epoch", save_strategy="epoch" ) trainer = Trainer( model=model, args=training_args, train_dataset=dataset["train"], eval_dataset=dataset["test"] ) trainer.train() # Zapisanie modelu model.save_pretrained("./layoutlmv3_finetuned")