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# Fine-Tuned BART Model for Text Classification on CNN News Articles
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[](https://huggingface.co/IT-community/Bart_News_text_classification)
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[](https://opensource.org/licenses/MIT)
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This is a fine-tuned BART (Bidirectional and Auto-Regressive Transformers) model for text classification on CNN news articles. The model was fine-tuned on a dataset of CNN news articles with labels indicating the article topic, using a batch size of 32, learning rate of 6e-5, and trained for one epoch.
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The model achieved the following performance metrics on the test set:
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Accuracy: 0.9591836734693877
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F1-score: 0.958301875401112
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Recall: 0.9591836734693877
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Precision: 0.9579673040369542
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## Contact
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# Fine-Tuned BART Model for Text Classification on CNN News Articles
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This is a fine-tuned BART (Bidirectional and Auto-Regressive Transformers) model for text classification on CNN news articles. The model was fine-tuned on a dataset of CNN news articles with labels indicating the article topic, using a batch size of 32, learning rate of 6e-5, and trained for one epoch.
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The model achieved the following performance metrics on the test set:
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Accuracy: 0.9591836734693877
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F1-score: 0.958301875401112
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Recall: 0.9591836734693877
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Precision: 0.9579673040369542
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## Contact
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