Add n_token_limit to dataset
#79
Merged
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I added a new parameter to the base dataset. If this parameter is set, after tokenisation, all instances in the dataset will be removed that have more than
n_token_limittokens. This allows to train models withmax_position_embeddings=n_token_limit+1. For instance, in ChEBI, 99% of instances have less than 300 SMILES tokens. Using that as a limit allows to reduce themax_position_embeddingsfrom 1800 (current default) to 301. This is useful for training runs as it allows as higher batch size and efficient memory usage. For "production models", I would recommend a higher number (e.g. 600 or 900)