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@@ -28,7 +28,7 @@ Complete details on the dataset can be found in our blog post [here](https://hug
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  ## Upsampling Experiment with Comparison to FineWeb
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  To evaluate the training efficiency of our dataset, we sampled 1.5T tokens from both FineWeb and TxT360 (using the aforementioned weighting) and conducted a training ablation on an 8x8B Mixture-of-Experts architecture, similar to Mixtral. We compared the learning curves by tracking training loss, validation scores, and performance across a wide array of diverse evaluation benchmarks. The validation set was sampled independently from SlimPajama. Note that this experiment is done on a slightly earlier version of the dataset.
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- <center><img src=" txttofineweb.png" alt="comparison" /></center>
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  ## Initial Data Representation
 
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  ## Upsampling Experiment with Comparison to FineWeb
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  To evaluate the training efficiency of our dataset, we sampled 1.5T tokens from both FineWeb and TxT360 (using the aforementioned weighting) and conducted a training ablation on an 8x8B Mixture-of-Experts architecture, similar to Mixtral. We compared the learning curves by tracking training loss, validation scores, and performance across a wide array of diverse evaluation benchmarks. The validation set was sampled independently from SlimPajama. Note that this experiment is done on a slightly earlier version of the dataset.
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+ <center><img src="txttofineweb.png" alt="comparison" /></center>
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  ## Initial Data Representation