--- library_name: Transformers tags: - text-classification - transformers - argilla --- # Model Card for *Model ID* This model has been created with [Argilla](https://docs.argilla.io), trained with *Transformers*. ## Model training Training the model using the `ArgillaTrainer`: ```python # Load the dataset: dataset = FeedbackDataset.from_argilla("...") # Create the training task: task = TrainingTask.for_text_classification(text=dataset.field_by_name("text"), label=dataset.question_by_name("question-3")) # Create the ArgillaTrainer: trainer = ArgillaTrainer( dataset=dataset, task=task, framework="transformers", model="bert-base-cased", ) trainer.update_config({ "logging_steps": 1, "num_train_epochs": 1 }) trainer.train(output_dir="None") ``` You can test the type of predictions of this model like so: ```python trainer.predict("This is awesome!") ``` ## Model Details ### Model Description - **Developed by:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ## Technical Specifications [optional] ### Framework Versions - Python: 3.10.7 - Argilla: 1.17.0-dev