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

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

Model trained with ArgillaTrainer for demo purposes

  • Developed by: [More Information Needed]
  • Shared by [optional]: [More Information Needed]
  • Model type: Finetuned version of prajjwal1/bert-tiny for demo purposes
  • Language(s) (NLP): ['en']
  • License: apache-2.0
  • Finetuned from model [optional]: prajjwal1/bert-tiny

Model Sources [optional]

  • Repository: N/A

Technical Specifications [optional]

Framework Versions

  • Python: 3.10.7
  • Argilla: 1.19.0-dev
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