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

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

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Safetensors

Model size

277M params

Tensor type

I64

F32

Inference Examples

Token Classification

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

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

Evaluation results

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

85.000
Dutch Test accuracy on Universal Dependencies v2.8
self-reported

81.600
German Test accuracy on Universal Dependencies v2.8
self-reported

82.600
Italian Test accuracy on Universal Dependencies v2.8
self-reported

82.500
French Test accuracy on Universal Dependencies v2.8
self-reported

83.100
Spanish Test accuracy on Universal Dependencies v2.8
self-reported

85.500
Russian Test accuracy on Universal Dependencies v2.8
self-reported

92.700
Swedish Test accuracy on Universal Dependencies v2.8
self-reported

89.500
Norwegian Test accuracy on Universal Dependencies v2.8
self-reported

84.500
Danish Test accuracy on Universal Dependencies v2.8
self-reported

88.400

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