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  # crumb/c4-benchfilter-nano
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- A derivation of the first 3M samples from the C4 dataset for a cheap and short continued pretraining for language models to optimize for benchmark scores without sacrificing generalization and generative modelling unrelated to chat or 'instruct' data.
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  The estimated top 10% of highest estimated length normalized ngram (mean of tri, quad, and penta-gram) overlaps for each of the
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  selected benchmark datasets (arc, truthful_qa, hellaswag, mmlu, humaneval) based
 
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  # crumb/c4-benchfilter-nano
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+ A 278k sample derivation of the first 3M samples from the C4 dataset for a cheap and short continued pretraining for language models to optimize for benchmark scores without sacrificing generalization and generative modelling unrelated to chat or 'instruct' data.
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  The estimated top 10% of highest estimated length normalized ngram (mean of tri, quad, and penta-gram) overlaps for each of the
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  selected benchmark datasets (arc, truthful_qa, hellaswag, mmlu, humaneval) based