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wietsedv
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xlm-roberta-base-ft-udpos28-af

Token Classification
Transformers
PyTorch
Safetensors
Afrikaans
xlm-roberta
part-of-speech
Eval Results
Inference Endpoints
Model card Files Community
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XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Afrikaans

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

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

Evaluation results

  • English Test accuracy on Universal Dependencies v2.8
    self-reported
    85.800
  • Dutch Test accuracy on Universal Dependencies v2.8
    self-reported
    83.700
  • German Test accuracy on Universal Dependencies v2.8
    self-reported
    83.600
  • Italian Test accuracy on Universal Dependencies v2.8
    self-reported
    84.400
  • French Test accuracy on Universal Dependencies v2.8
    self-reported
    83.100
  • Spanish Test accuracy on Universal Dependencies v2.8
    self-reported
    86.700
  • Russian Test accuracy on Universal Dependencies v2.8
    self-reported
    86.400
  • Swedish Test accuracy on Universal Dependencies v2.8
    self-reported
    87.700
  • Norwegian Test accuracy on Universal Dependencies v2.8
    self-reported
    81.300
  • Danish Test accuracy on Universal Dependencies v2.8
    self-reported
    86.800
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