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

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

Downloads last month: 17

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-fo

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

Evaluation results

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

86.400
Dutch Test accuracy on Universal Dependencies v2.8
self-reported

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

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

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

80.600
Spanish Test accuracy on Universal Dependencies v2.8
self-reported

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

83.600
Swedish Test accuracy on Universal Dependencies v2.8
self-reported

87.300
Norwegian Test accuracy on Universal Dependencies v2.8
self-reported

83.900
Danish Test accuracy on Universal Dependencies v2.8
self-reported

87.500

View on Papers With Code