Hugging Face's logo

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

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

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")
Downloads last month
3
Safetensors
Model size
0.3B params
Tensor type
I64
·
F32
·
Inference Providers NEW
Token Classification
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

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