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XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Old Church Slavonic

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-cu")
model = AutoModelForTokenClassification.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-cu")
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Safetensors
Model size
277M params
Tensor type
I64
·
F32
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Dataset used to train wietsedv/xlm-roberta-base-ft-udpos28-cu

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

Evaluation results

  • English Test accuracy on Universal Dependencies v2.8
    self-reported
    60.100
  • Dutch Test accuracy on Universal Dependencies v2.8
    self-reported
    58.700
  • German Test accuracy on Universal Dependencies v2.8
    self-reported
    59.900
  • Italian Test accuracy on Universal Dependencies v2.8
    self-reported
    55.800
  • French Test accuracy on Universal Dependencies v2.8
    self-reported
    59.500
  • Spanish Test accuracy on Universal Dependencies v2.8
    self-reported
    58.400
  • Russian Test accuracy on Universal Dependencies v2.8
    self-reported
    63.200
  • Swedish Test accuracy on Universal Dependencies v2.8
    self-reported
    64.500
  • Norwegian Test accuracy on Universal Dependencies v2.8
    self-reported
    58.000
  • Danish Test accuracy on Universal Dependencies v2.8
    self-reported
    59.900