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mlm-spanish-roberta-base

This model has a RoBERTa base architecture and was trained from scratch with 3.6 GB of raw text over 10 epochs. 4 Tesla V-100 GPUs were used for the training.

To test the quality of the resulting model we evaluate it over the GLUES benchmark for Spanish NLU. The results are the following:

Task Score (metric)
XNLI 71.99 (accuracy)
Paraphrasing 74.85 (accuracy)
NER 85.34 (F1)
POS 97.49 (accuracy)
Dependency Parsing 85.14/81.08 (UAS/LAS)
Document Classification 93.00 (accuracy)
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