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

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

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Inference Examples

Token Classification

Inference API (serverless) is not available, repository is disabled.

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

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

Evaluation results

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

60.900
Dutch Test accuracy on Universal Dependencies v2.8
self-reported

57.800
German Test accuracy on Universal Dependencies v2.8
self-reported

61.000
Italian Test accuracy on Universal Dependencies v2.8
self-reported

59.400
French Test accuracy on Universal Dependencies v2.8
self-reported

53.900
Spanish Test accuracy on Universal Dependencies v2.8
self-reported

55.500
Russian Test accuracy on Universal Dependencies v2.8
self-reported

71.600
Swedish Test accuracy on Universal Dependencies v2.8
self-reported

65.900
Norwegian Test accuracy on Universal Dependencies v2.8
self-reported

63.000
Danish Test accuracy on Universal Dependencies v2.8
self-reported

64.400

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