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@@ -90,13 +90,12 @@ The high signal tasks also show lower coefficient of variation compared to the
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    **Evaluation Results**
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- <img src="fig7.jpg" alt="fig7.jpg" style="width:1000px;"/>
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  **Combining GneissWeb Components into a Winning Recipe**
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  There are various ways to combine the key ingredients and build a recipe, including deciding which components to include and their order as well as designing ensemble filtering rules using multiple quality annotators. We performed rigorous ablations by combining the key ingredients in multiple variations and sequences with the aim of maximizing downstream task performance under the constraint of retaining at least 10T tokens from FineWeb.V1.1.0.
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- ![](Ingredients.png)
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  <img src="Ingredients.png" alt="Ingredients.png" style="width:1000px;"/>
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  Figure 19 : Key ingredients selected for building the GneissWeb recipe
 
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  &nbsp;&nbsp;**Evaluation Results**
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+ <img src="fig7.jpg" alt="fig7.jpg" style="width:1400px;"/>
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  **Combining GneissWeb Components into a Winning Recipe**
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  There are various ways to combine the key ingredients and build a recipe, including deciding which components to include and their order as well as designing ensemble filtering rules using multiple quality annotators. We performed rigorous ablations by combining the key ingredients in multiple variations and sequences with the aim of maximizing downstream task performance under the constraint of retaining at least 10T tokens from FineWeb.V1.1.0.
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  <img src="Ingredients.png" alt="Ingredients.png" style="width:1000px;"/>
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  Figure 19 : Key ingredients selected for building the GneissWeb recipe