movie-genre-classifier

Model Card for Model ID

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Model Details

Model Description

This model is a DistilBERT-based text classification model fine-tuned to predict movie genres from plot summaries.

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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

• Developed by: Raissa Turu
• Model type: DistilBERT. Text classification
• Language(s) (NLP): English
• License: Apache 2.0
• Finetuned from model [optional]: distilbert-base-uncased

Uses

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Automatically classify movies by genre from plot summaries. This model is intended for educational and academic purposes, such as demonstrating NLP text classification and fine-tuning transformer models.

Direct Use

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from transformers import DistilBertTokenizerFast, DistilBertForSequenceClassification, pipeline

tokenizer = DistilBertTokenizerFast.from_pretrained("Raissa2502/movie-genre-classifier")
model = DistilBertForSequenceClassification.from_pretrained("Raissa2502/movie-genre-classifier")

classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)

prediction = classifier(
    "A young wizard discovers he has magical powers and attends a school for wizards."
)

print(prediction)

Bias, Risks, and Limitations

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• Movie plots may belong to multiple genres, but the model predicts only one.
• Performance depends on the quality and balance of the training data.

Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

Training Details

3 epochs, batch size 8, learning rate 5e-5

Testing Data, Factors & Metrics

Metrics

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The model was evaluated using:

• Accuracy
• Weighted F1-score

These metrics are appropriate for multi-class genre classification and help measure overall performance while accounting for class imbalance.