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

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

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Inference Examples

Token Classification

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

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

Evaluation results

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

82.400
Dutch Test accuracy on Universal Dependencies v2.8
self-reported

83.400
German Test accuracy on Universal Dependencies v2.8
self-reported

75.500
Italian Test accuracy on Universal Dependencies v2.8
self-reported

82.700
French Test accuracy on Universal Dependencies v2.8
self-reported

82.000
Spanish Test accuracy on Universal Dependencies v2.8
self-reported

86.100
Russian Test accuracy on Universal Dependencies v2.8
self-reported

84.100
Swedish Test accuracy on Universal Dependencies v2.8
self-reported

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

79.900
Danish Test accuracy on Universal Dependencies v2.8
self-reported

81.900

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