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README.md
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@@ -103,6 +103,8 @@ For those in the greater than 5 Trillion token set size, in Fig 8 we show the pe
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In Fig 9, we show the progression of accuracy with training for High Signal Tasks for 1.4 billion parameter model for 350 billion tokens. We see that for all three datasets compared, the accuracy increases over time and the accuracy of GneissWeb is consistently higher than FineWeb and FineWeb-Edu-score-2.
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**Figure 9:** Average evaluation score on High-Signal tasks versus the number of tokens for 1.4 Billion parameter models. The model trained on GneissWeb consistently outperforms the ones trained on FineWeb.V1.1 and FineWeb-Edu-score-2.
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**At 3 and 7 Billion Model Size with 100 Billion Tokens**
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In Fig 9, we show the progression of accuracy with training for High Signal Tasks for 1.4 billion parameter model for 350 billion tokens. We see that for all three datasets compared, the accuracy increases over time and the accuracy of GneissWeb is consistently higher than FineWeb and FineWeb-Edu-score-2.
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<img src="1.4Bmodels_100B.png" alt="1.4Bmodels_100B.png" style="width:1000px;"/>
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**Figure 9:** Average evaluation score on High-Signal tasks versus the number of tokens for 1.4 Billion parameter models. The model trained on GneissWeb consistently outperforms the ones trained on FineWeb.V1.1 and FineWeb-Edu-score-2.
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**At 3 and 7 Billion Model Size with 100 Billion Tokens**
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