LEGALECTRA (base) is an Electra like model (discriminator in this case) trained on
A collection of corpora of Spanish legal domain.
As mentioned in the original
paper:
ELECTRA is a new method for self-supervised language representation learning. It can be used to pre-train transformer networks using relatively little compute. ELECTRA models are trained to distinguish "real" input tokens vs "fake" input tokens generated by another neural network, similar to the discriminator of a
GAN. At small scale, ELECTRA achieves strong results even when trained on a single GPU. At large scale, ELECTRA achieves state-of-the-art results on the
SQuAD 2.0 dataset.
For a detailed description and experimental results, please refer the paper
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators.
