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# mlm-spanish-roberta-base
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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.
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To test the quality of the resulting model we evaluate it over the [GLUES](https://github.com/dccuchile/GLUES) benchmark for Spanish NLU. The results are the following:
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| Tarea | Score (metric) |
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| XNLI | 71.99 (accuracy) |
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| Paraphrasing | 74.85 (accuracy) |
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| NER | 85.34 (F1) |
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| POS | 97.49 (accuracy) |
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| Dependency Parsing | 85.14/81.08 (UAS/LAS) |
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| Document Classification | 93.00 (accuracy) |
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