nlp text-classification argilla transformers

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Model Card for Model ID

This model has been created with Argilla, trained with Transformers.

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This is a sample model finetuned from prajjwal1/bert-tiny.

Model training

Training the model using the ArgillaTrainer:

# Load the dataset:
dataset = FeedbackDataset.from_huggingface("argilla/emotion")

# Create the training task:
task = TrainingTask.for_text_classification(text=dataset.field_by_name("text"), label=dataset.question_by_name("label"))

# Create the ArgillaTrainer:
trainer = ArgillaTrainer(
    dataset=dataset,
    task=task,
    framework="transformers",
    model="prajjwal1/bert-tiny",
)

trainer.update_config({
    "logging_steps": 1,
    "num_train_epochs": 1,
    "output_dir": "tmp"
})

trainer.train(output_dir="None")

You can test the type of predictions of this model like so:

trainer.predict("This is awesome!")

Model Details

Model Description

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Model trained with ArgillaTrainer for demo purposes

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Training Details

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Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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