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wietsedv
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xlm-roberta-base-ft-udpos28-he

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

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

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

  • English Test accuracy on Universal Dependencies v2.8
    self-reported
    76.600
  • Dutch Test accuracy on Universal Dependencies v2.8
    self-reported
    73.700
  • German Test accuracy on Universal Dependencies v2.8
    self-reported
    70.500
  • Italian Test accuracy on Universal Dependencies v2.8
    self-reported
    75.100
  • French Test accuracy on Universal Dependencies v2.8
    self-reported
    71.300
  • Spanish Test accuracy on Universal Dependencies v2.8
    self-reported
    74.500
  • Russian Test accuracy on Universal Dependencies v2.8
    self-reported
    80.300
  • Swedish Test accuracy on Universal Dependencies v2.8
    self-reported
    79.300