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CV fine-tuning: trainer configuration

Now that you have prepared the dataset and adapted a pretrained model to the new classes, it is time to configure your trainer.

The TrainingArguments and Trainer have been loaded from the transformers library. The model (model) and dataset (dataset) have been loaded as you previously configured them.

Diese Übung ist Teil des Kurses

Multi-Modal Models with Hugging Face

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Anleitung zur Übung

  • Adjust the learning rate to 6e-5.
  • Provide the model, training data, and test data to the Trainer instance.

Interaktive Übung

Vervollständige den Beispielcode, um diese Übung erfolgreich abzuschließen.

training_args = TrainingArguments(
    output_dir="dataset_finetune",
    # Adjust the learning rate
    ____,
    gradient_accumulation_steps=4,
    num_train_epochs=3,
    push_to_hub=False
)

trainer = Trainer(
    # Provide the model and datasets
    model=____,
    args=training_args,
    data_collator=data_collator,
    train_dataset=____,
    eval_dataset=____,
    processing_class=image_processor,
    compute_metrics=compute_metrics,
)
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