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KoQuality-Polyglot-5.8b is a fine-tuned version of [EleutherAI/polyglot-ko-5.8b](https://huggingface.co/EleutherAI/polyglot-ko-5.8b) on [KoQuality dataset](https://huggingface.co/datasets/DILAB-HYU/KoQuality), which is curated by proposed method (len_group=5, k=100, n=0.01, method=ppl_sampling).
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### Average accuracy score of the KoBEST datasets
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We use [KoBEST benchmark](https://huggingface.co/datasets/skt/kobest_v1) datasets(BoolQ, COPA, HellaSwag, SentiNeg, WiC) to compare the performance of our best model and other models accuracy. Our model outperforms other models in the average accuracy score of the KoBEST datasets.
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<img src=https://cdn-uploads.huggingface.co/production/uploads/650fecfd247f564485f8fbcf/q4cCUCzRJa3m2f7oxI_FY.png style="max-width: 500px; width: 300%"/>
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| Model | 0-shot | 1-shot | 2-shot | 5-shot | 10-shot
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| koquality-polyglot-5.8b | 0.5472 | 0.5979 | 0.6260 | 0.6486 | 0.6535
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KoQuality-Polyglot-5.8b is a fine-tuned version of [EleutherAI/polyglot-ko-5.8b](https://huggingface.co/EleutherAI/polyglot-ko-5.8b) on [KoQuality dataset](https://huggingface.co/datasets/DILAB-HYU/KoQuality), which is curated by proposed method (len_group=5, k=100, n=0.01, method=ppl_sampling).
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### Overall Average accuracy score of the KoBEST datasets
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We use [KoBEST benchmark](https://huggingface.co/datasets/skt/kobest_v1) datasets(BoolQ, COPA, HellaSwag, SentiNeg, WiC) to compare the performance of our best model and other models accuracy. Our model outperforms other models in the average accuracy score of the KoBEST datasets.
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<img src=https://cdn-uploads.huggingface.co/production/uploads/650fecfd247f564485f8fbcf/q4cCUCzRJa3m2f7oxI_FY.png style="max-width: 500px; width: 300%"/>
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| Model | 0-shot | 1-shot | 2-shot | 5-shot | 10-shot
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| koquality-polyglot-5.8b | 0.5472 | 0.5979 | 0.6260 | 0.6486 | 0.6535
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