XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Old Church Slavonic

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

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Safetensors

Model size

277M params

Tensor type

I64

F32

Inference Providers NEW

Token Classification

This model is not currently available via any of the supported third-party Inference Providers, and the model is not deployed on the HF Inference API.

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

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

Evaluation results

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

60.100
Dutch Test accuracy on Universal Dependencies v2.8
self-reported

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

59.900
Italian Test accuracy on Universal Dependencies v2.8
self-reported

55.800
French Test accuracy on Universal Dependencies v2.8
self-reported

59.500
Spanish Test accuracy on Universal Dependencies v2.8
self-reported

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

63.200
Swedish Test accuracy on Universal Dependencies v2.8
self-reported

64.500
Norwegian Test accuracy on Universal Dependencies v2.8
self-reported

58.000
Danish Test accuracy on Universal Dependencies v2.8
self-reported

59.900

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