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XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Arabic

This model is part of our paper called:

  • Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages

Check the Space for more details.

Usage

from transformers import AutoTokenizer, AutoModelForTokenClassification

tokenizer = AutoTokenizer.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-ar")
model = AutoModelForTokenClassification.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-ar")
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Dataset used to train wietsedv/xlm-roberta-base-ft-udpos28-ar

Space using wietsedv/xlm-roberta-base-ft-udpos28-ar 1

Evaluation results

  • English Test accuracy on Universal Dependencies v2.8
    self-reported
    62.800
  • Dutch Test accuracy on Universal Dependencies v2.8
    self-reported
    63.500
  • German Test accuracy on Universal Dependencies v2.8
    self-reported
    63.800
  • Italian Test accuracy on Universal Dependencies v2.8
    self-reported
    60.200
  • French Test accuracy on Universal Dependencies v2.8
    self-reported
    58.500
  • Spanish Test accuracy on Universal Dependencies v2.8
    self-reported
    64.900
  • Russian Test accuracy on Universal Dependencies v2.8
    self-reported
    77.200
  • Swedish Test accuracy on Universal Dependencies v2.8
    self-reported
    68.500
  • Norwegian Test accuracy on Universal Dependencies v2.8
    self-reported
    64.600
  • Danish Test accuracy on Universal Dependencies v2.8
    self-reported
    66.100