This checkpoint has been trained for the XNLI dataset.
This checkpoint was created from
Bertin Gaussian 512, which is a
RoBERTa-base model trained from scratch in Spanish. Information on this base model may be found at
its own card and at deeper detail on
the main project card.
The training dataset for the base model is
mc4 subsampling documents to a total of about 50 million examples. Sampling is biased towards average perplexity values (using a Gaussian function), discarding more often documents with very large values (poor quality) of very small values (short, repetitive texts).
