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

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

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

Evaluation results

  • English Test accuracy on Universal Dependencies v2.8
    self-reported
    83.000
  • Dutch Test accuracy on Universal Dependencies v2.8
    self-reported
    81.900
  • German Test accuracy on Universal Dependencies v2.8
    self-reported
    83.900
  • Italian Test accuracy on Universal Dependencies v2.8
    self-reported
    80.900
  • French Test accuracy on Universal Dependencies v2.8
    self-reported
    79.200
  • Spanish Test accuracy on Universal Dependencies v2.8
    self-reported
    80.900
  • Russian Test accuracy on Universal Dependencies v2.8
    self-reported
    89.100
  • Swedish Test accuracy on Universal Dependencies v2.8
    self-reported
    86.200
  • Norwegian Test accuracy on Universal Dependencies v2.8
    self-reported
    80.600
  • Danish Test accuracy on Universal Dependencies v2.8
    self-reported
    84.800