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Overall Performance:
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MSH-v1 achieves a higher average score of 71.18% compared to Bielik v2.3's 69.33%, demonstrating the effectiveness of our checkpoint merging technique in improving model performance across diverse NLP tasks.
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All evaluations were conducted using the Open PL LLM Leaderboard framework (0-shot) as part of the SpeakLeash.org open-science initiative.
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Overall Performance:
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MSH-v1 achieves a higher average score of 71.18% compared to Bielik v2.3's 69.33%, demonstrating the effectiveness of our checkpoint merging technique in improving model performance across diverse NLP tasks.
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All evaluations were conducted using the Open PL LLM Leaderboard framework (0-shot) as part of the SpeakLeash.org open-science initiative.
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Kudos to the **SpeakLeash** project and **ACK Cyfronet AGH** for their extraordinary work.
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