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wietsedv
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xlm-roberta-base-ft-udpos28-zh

Token Classification
Transformers
PyTorch
Safetensors
Chinese
xlm-roberta
part-of-speech
Eval Results (legacy)
Model card Files
xet
 Community
1

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

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-zh")
model = AutoModelForTokenClassification.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-zh")
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Evaluation results

  • English Test accuracy on Universal Dependencies v2.8
    self-reported
    60.200
  • Dutch Test accuracy on Universal Dependencies v2.8
    self-reported
    56.900
  • German Test accuracy on Universal Dependencies v2.8
    self-reported
    57.500
  • Italian Test accuracy on Universal Dependencies v2.8
    self-reported
    57.300
  • French Test accuracy on Universal Dependencies v2.8
    self-reported
    54.100
  • Spanish Test accuracy on Universal Dependencies v2.8
    self-reported
    54.400
  • Russian Test accuracy on Universal Dependencies v2.8
    self-reported
    69.600
  • Swedish Test accuracy on Universal Dependencies v2.8
    self-reported
    61.800