Add dataset_shard_num and dataset_shard_idx
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@@ -209,6 +209,10 @@ dataset_prepared_path: data/last_run_prepared
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push_dataset_to_hub: # repo path
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# How much of the dataset to set aside as evaluation. 1 = 100%, 0.50 = 50%, etc
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val_set_size: 0.04
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# Num shards for whole dataset
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dataset_shard_num:
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# Index of shard to use for whole dataset
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dataset_shard_idx:
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# the maximum length of an input to train with, this should typically be less than 2048
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# as most models have a token/context limit of 2048
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