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

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

Downloads last month: 3

Inference Examples

Token Classification

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-hr

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

Evaluation results

English Test accuracy on Universal Dependencies v2.8
self-reported

83.700
Dutch Test accuracy on Universal Dependencies v2.8
self-reported

83.700
German Test accuracy on Universal Dependencies v2.8
self-reported

83.200
Italian Test accuracy on Universal Dependencies v2.8
self-reported

83.200
French Test accuracy on Universal Dependencies v2.8
self-reported

84.200
Spanish Test accuracy on Universal Dependencies v2.8
self-reported

87.800
Russian Test accuracy on Universal Dependencies v2.8
self-reported

91.400
Swedish Test accuracy on Universal Dependencies v2.8
self-reported

85.400
Norwegian Test accuracy on Universal Dependencies v2.8
self-reported

79.000
Danish Test accuracy on Universal Dependencies v2.8
self-reported

83.800

View on Papers With Code