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

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

Downloads last month: 227

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-te

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

Evaluation results

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

68.900
Dutch Test accuracy on Universal Dependencies v2.8
self-reported

68.000
German Test accuracy on Universal Dependencies v2.8
self-reported

67.000
Italian Test accuracy on Universal Dependencies v2.8
self-reported

63.300
French Test accuracy on Universal Dependencies v2.8
self-reported

62.100
Spanish Test accuracy on Universal Dependencies v2.8
self-reported

63.100
Russian Test accuracy on Universal Dependencies v2.8
self-reported

71.000
Swedish Test accuracy on Universal Dependencies v2.8
self-reported

66.400
Norwegian Test accuracy on Universal Dependencies v2.8
self-reported

62.100
Danish Test accuracy on Universal Dependencies v2.8
self-reported

67.500

View on Papers With Code