metadata
license: apache-2.0
language:
- es
metrics:
- accuracy
tags:
- lemmatization
Model Card for xlm-roberta-large-lemma-es
This model is a fine-tuned version of xlm-roberta-large for the contextual lemmatization task.
The datasets used for training are extracted from the data of the SIGMORPHON 2019 Shared Task.
The model for the Spanish language was trained using GSD corpus.
Training Hyperparameters
SEED: 42
EPOCHS: 20
BATCH SIZE: 4
GRADIENT ACCUMULATION STEPS: 2
LEARNING RATE: 0.00002
WARMUP: 0.06
WEIGHT DECAY: 0.1
Results
For more details you can see the paper and the repository:
- 📖 Paper: On the Role of Morphological Information for Contextual Lemmatization
- 🌐 Repository: Datasets and training files
Contact: Olia Toporkov and Rodrigo Agerri HiTZ Center - Ixa, University of the Basque Country UPV/EHU
Funding:
Model type: xlm-roberta-large
Language(s) (NLP): Spanish
License: apache-2.0
Citation
@article{10.1162/coli_a_00497,
author = {Toporkov, Olia and Agerri, Rodrigo},
title = "{On the Role of Morphological Information for Contextual
Lemmatization}",
journal = {Computational Linguistics},
volume = {50},
number = {1},
pages = {157-191},
year = {2024},
month = {03},
issn = {0891-2017},
doi = {10.1162/coli_a_00497},
url = {https://doi.org/10.1162/coli\_a\_00497},
eprint = {https://direct.mit.edu/coli/article-pdf/50/1/157/2367156/coli\_a\_00497.pdf},
}