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Doge-20M

Text Generation
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Safetensors
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doge
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@@ -45,10 +45,10 @@ In addition, Doge uses Dynamic Mask Attention as sequence transformation and can
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  **Evaluation**:
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- | Model | MMLU | TriviaQA | ARC-E | ARC-C | PIQA | HellaSwag | OBQA | Winogrande |
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- | [Doge-20M](https://huggingface.co/JingzeShi/Doge-20M) | 25.43 | 0 | 36.83 | 22.53 | 58.38 | 27.25 | 25.60 | 50.20 |
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- | [Doge-60M](https://huggingface.co/JingzeShi/Doge-60M) | 26.41 | 0 | 50.00 | 25.34 | 61.43 | 31.45 | 28.00 | 49.64 |
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  > All evaluations are done using five-shot settings, without additional training on the benchmarks.
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  **Evaluation**:
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+ | Model | MMLU | TriviaQA | ARC-E | ARC-C | PIQA | HellaSwag | OBQA | Winogrande | tokens / s on CPU |
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+ |---|---|---|---|---|---|---|---|---|---|
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+ | [Doge-20M](https://huggingface.co/JingzeShi/Doge-20M) | 25.43 | 0 | 36.83 | 22.53 | 58.38 | 27.25 | 25.60 | 50.20 | 142 |
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+ | [Doge-60M](https://huggingface.co/JingzeShi/Doge-60M) | 26.41 | 0 | 50.00 | 25.34 | 61.43 | 31.45 | 28.00 | 49.64 | 62 |
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  > All evaluations are done using five-shot settings, without additional training on the benchmarks.
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