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The current version of the fine-tuned model outperforms the base model [facebook/bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli) by 23 percentage points (57% accuracy vs 34% accuracy) in a test set with 10 candidate zero-shot classes (the most frequent categories in the test split of [reddgr/nli-chatbot-prompt-categorization](https://huggingface.co/datasets/reddgr/nli-chatbot-prompt-categorization)).
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The dataset and the model are continously updated as they assist with content publishing on my website [Talking to Chatbots](https://talkingtochatbots)
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The current version of the fine-tuned model outperforms the base model [facebook/bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli) by 23 percentage points (57% accuracy vs 34% accuracy) in a test set with 10 candidate zero-shot classes (the most frequent categories in the test split of [reddgr/nli-chatbot-prompt-categorization](https://huggingface.co/datasets/reddgr/nli-chatbot-prompt-categorization)).
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The chart below compares the results for the 12 most popular candidate classes in the Test split:
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![Zero-shot prompt classification confusion matrix for reddgr/zero-shot-prompt-classifier-bart-ft](https://talkingtochatbots.com/wp-content/uploads/2024/12/zero-shot-prompt-classification-comparison-12-classes-56-accuracy.png)
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The dataset and the model are continously updated as they assist with content publishing on my website [Talking to Chatbots](https://talkingtochatbots)
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