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

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

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

Evaluation results

  • English Test accuracy on Universal Dependencies v2.8
    self-reported
    89.100
  • Dutch Test accuracy on Universal Dependencies v2.8
    self-reported
    89.400
  • German Test accuracy on Universal Dependencies v2.8
    self-reported
    83.400
  • Italian Test accuracy on Universal Dependencies v2.8
    self-reported
    96.300
  • French Test accuracy on Universal Dependencies v2.8
    self-reported
    92.200
  • Spanish Test accuracy on Universal Dependencies v2.8
    self-reported
    94.000
  • Russian Test accuracy on Universal Dependencies v2.8
    self-reported
    90.500
  • Swedish Test accuracy on Universal Dependencies v2.8
    self-reported
    91.100
  • Norwegian Test accuracy on Universal Dependencies v2.8
    self-reported
    84.700
  • Danish Test accuracy on Universal Dependencies v2.8
    self-reported
    91.600