Edit model card

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

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-el")
model = AutoModelForTokenClassification.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-el")
Downloads last month
14
Safetensors
Model size
277M params
Tensor type
I64
·
F32
·
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-el

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

Evaluation results

  • English Test accuracy on Universal Dependencies v2.8
    self-reported
    83.600
  • Dutch Test accuracy on Universal Dependencies v2.8
    self-reported
    82.200
  • German Test accuracy on Universal Dependencies v2.8
    self-reported
    82.600
  • Italian Test accuracy on Universal Dependencies v2.8
    self-reported
    82.000
  • French Test accuracy on Universal Dependencies v2.8
    self-reported
    78.700
  • Spanish Test accuracy on Universal Dependencies v2.8
    self-reported
    82.200
  • Russian Test accuracy on Universal Dependencies v2.8
    self-reported
    88.400
  • Swedish Test accuracy on Universal Dependencies v2.8
    self-reported
    87.400
  • Norwegian Test accuracy on Universal Dependencies v2.8
    self-reported
    82.100
  • Danish Test accuracy on Universal Dependencies v2.8
    self-reported
    85.900