Edit model card

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

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-hu")
model = AutoModelForTokenClassification.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-hu")
Downloads last month
10
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

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

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

Evaluation results

  • English Test accuracy on Universal Dependencies v2.8
    self-reported
    77.000
  • Dutch Test accuracy on Universal Dependencies v2.8
    self-reported
    77.000
  • German Test accuracy on Universal Dependencies v2.8
    self-reported
    77.000
  • Italian Test accuracy on Universal Dependencies v2.8
    self-reported
    77.600
  • French Test accuracy on Universal Dependencies v2.8
    self-reported
    75.900
  • Spanish Test accuracy on Universal Dependencies v2.8
    self-reported
    76.100
  • Russian Test accuracy on Universal Dependencies v2.8
    self-reported
    78.700
  • Swedish Test accuracy on Universal Dependencies v2.8
    self-reported
    78.900
  • Norwegian Test accuracy on Universal Dependencies v2.8
    self-reported
    74.600
  • Danish Test accuracy on Universal Dependencies v2.8
    self-reported
    77.700