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- Accuracy: 0.5471
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- F1 Binary Minimum3: 0.7028
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While the macro F1 scores across the 1-5 rating scale are relatively low due to the model's difficulty in distinguishing between higher-rated samples, the classifier performs well for our primary filtering task. When converting to binary classification, using a threshold of 2 achieves the F1 scores ranges between 0.8 and 0.9 for most Stack-Edu classifiers, whereas a threshold of 3 yields F1 scores between 0.55 and 0.70. With the Highest being C
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### Training hyperparameters
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The following hyperparameters were used during training:
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- Accuracy: 0.5471
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- F1 Binary Minimum3: 0.7028
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While the macro F1 scores across the 1-5 rating scale are relatively low due to the model's difficulty in distinguishing between higher-rated samples, the classifier performs well for our primary filtering task. When converting to binary classification, using a threshold of 2 achieves the F1 scores ranges between 0.8 and 0.9 for most Stack-Edu classifiers, whereas a threshold of 3 yields F1 scores between 0.55 and 0.70. With the Highest being Python, C, Rust and the lowest being TypeScript and PHP.
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<div style="display: flex; justify-content: center; gap: 20px;">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/61c141342aac764ce1654e43/z0lCnH2nqYMu09JsxPvFb.png" width="600">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/61c141342aac764ce1654e43/W6BQO6Rkafpj-96fWdCOv.png" width="600">
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</div>
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We validated these classifiers by filtering Stack v2 data and testing on an intermediate SmolLM2 checkpoint. Filtering with a threshold of 3 improved performance across most languages while maintaining adequate data volume, though Java showed better results with a threshold of 2.
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### Training hyperparameters
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The following hyperparameters were used during training:
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