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")

Downloads last month: 14

Safetensors

Model size

277M params

Tensor type

I64

F32

Inference Examples

Token Classification

This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

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

View on Papers With Code