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Added open llm benchmark results table.
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README.md
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@@ -19,7 +19,13 @@ A linear merge of:
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These three models showed excellent acumen in technical topics so I wanted to see how they would behave together in a merge. Several different ratios were tested before this release, in the end a higher weighting for merlinite-7b helped smooth out some edges. This model is a test of how LAB tuning is impacted by merges with models leveraging DPO.
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This was my first experiment with merging models so any feedback is greatly appreciated.
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These three models showed excellent acumen in technical topics so I wanted to see how they would behave together in a merge. Several different ratios were tested before this release, in the end a higher weighting for merlinite-7b helped smooth out some edges. This model is a test of how LAB tuning is impacted by merges with models leveraging DPO.
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### Benchmark Performance
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| Name | Avg. | ARC | HellaSwag | MMLU | TruthfulQA | Winograde | GSM8K |
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| ---- | ---- | ---- | ---- | ---- | ---- | ---- | ---- |
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| <b>Magic-Dolphin-7b</b> | <u><b>67.48</b></u> | 65.78 | 85.61 | 64.64 | 58.01 | <u><b>79.64</b></u> | <u><b>51.18</b></u> |
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| dolphin-2.6-mistral-7b-dpo-laser | 67.28 | 66.3 | 85.73 | 63.16 | 61.71 | 79.16 | 47.61 |
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| merlinite-7b | N/A | 63.99 | 84.37 | 64.88 | N/A | 78.24 | N/A |
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| Hyperion-1.5-Mistral-7B | 61.43 | 60.49 | 83.64 | 63.57 | 41.78 | 78.61 | 40.49 |
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This was my first experiment with merging models so any feedback is greatly appreciated.
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