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

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

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Safetensors

Model size

277M params

Tensor type

I64

F32

Token Classification

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

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

Evaluation results

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

57.200
Dutch Test accuracy on Universal Dependencies v2.8
self-reported

58.400
German Test accuracy on Universal Dependencies v2.8
self-reported

57.700
Italian Test accuracy on Universal Dependencies v2.8
self-reported

57.300
French Test accuracy on Universal Dependencies v2.8
self-reported

53.800
Spanish Test accuracy on Universal Dependencies v2.8
self-reported

58.700
Russian Test accuracy on Universal Dependencies v2.8
self-reported

66.900
Swedish Test accuracy on Universal Dependencies v2.8
self-reported

59.300
Norwegian Test accuracy on Universal Dependencies v2.8
self-reported

56.700
Danish Test accuracy on Universal Dependencies v2.8
self-reported

59.300

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