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

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-id")
model = AutoModelForTokenClassification.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-id")
Downloads last month
9
Inference Providers NEW
This model is not currently available via any of the supported Inference Providers.

Dataset used to train wietsedv/xlm-roberta-base-ft-udpos28-id

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

Evaluation results

  • English Test accuracy on Universal Dependencies v2.8
    self-reported
    82.400
  • Dutch Test accuracy on Universal Dependencies v2.8
    self-reported
    83.400
  • German Test accuracy on Universal Dependencies v2.8
    self-reported
    75.500
  • Italian Test accuracy on Universal Dependencies v2.8
    self-reported
    82.700
  • French Test accuracy on Universal Dependencies v2.8
    self-reported
    82.000
  • Spanish Test accuracy on Universal Dependencies v2.8
    self-reported
    86.100
  • Russian Test accuracy on Universal Dependencies v2.8
    self-reported
    84.100
  • Swedish Test accuracy on Universal Dependencies v2.8
    self-reported
    83.200
  • Norwegian Test accuracy on Universal Dependencies v2.8
    self-reported
    79.900
  • Danish Test accuracy on Universal Dependencies v2.8
    self-reported
    81.900