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README.md
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The `Locutusque/Hyperion-2.0-Mistral-7B` model was fine-tuned on the Hyperion-v2.0 dataset, which amalgamates various datasets rich in diversity and complexity, including programming, medical texts, mathematical problems, and reasoning tasks.
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## Evaluation Results
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## How to Use
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```python
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The `Locutusque/Hyperion-2.0-Mistral-7B` model was fine-tuned on the Hyperion-v2.0 dataset, which amalgamates various datasets rich in diversity and complexity, including programming, medical texts, mathematical problems, and reasoning tasks.
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## Evaluation Results
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0-shot AGIEval
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| Tasks |Version|Filter|n-shot| Metric |Value | |Stderr|
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|---------------------------------|-------|------|-----:|--------|-----:|---|-----:|
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|agieval_nous |N/A |none | 0|acc |0.3602|± |0.0929|
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| | |none | 0|acc_norm|0.3342|± |0.0764|
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| - agieval_aqua_rat | 1|none | 0|acc |0.2402|± |0.0269|
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| | |none | 0|acc_norm|0.2441|± |0.0270|
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| - agieval_logiqa_en | 1|none | 0|acc |0.2965|± |0.0179|
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| | |none | 0|acc_norm|0.3226|± |0.0183|
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| - agieval_lsat_ar | 1|none | 0|acc |0.2348|± |0.0280|
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| | |none | 0|acc_norm|0.2000|± |0.0264|
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| - agieval_lsat_lr | 1|none | 0|acc |0.3667|± |0.0214|
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| | |none | 0|acc_norm|0.3373|± |0.0210|
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| - agieval_lsat_rc | 1|none | 0|acc |0.4981|± |0.0305|
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| | |none | 0|acc_norm|0.4089|± |0.0300|
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| - agieval_sat_en | 1|none | 0|acc |0.6359|± |0.0336|
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| | |none | 0|acc_norm|0.5777|± |0.0345|
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| - agieval_sat_en_without_passage| 1|none | 0|acc |0.3883|± |0.0340|
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| | |none | 0|acc_norm|0.3544|± |0.0334|
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| - agieval_sat_math | 1|none | 0|acc |0.3500|± |0.0322|
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| | |none | 0|acc_norm|0.2682|± |0.0299|
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| Groups |Version|Filter|n-shot| Metric |Value | |Stderr|
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|------------|-------|------|-----:|--------|-----:|---|-----:|
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|agieval_nous|N/A |none | 0|acc |0.3602|± |0.0929|
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| | |none | 0|acc_norm|0.3342|± |0.0764|
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5-shot AGIEval coming soon.
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## How to Use
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```python
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