metadata

datasets:
  - cjvt/si_nli
language:
  - sl
license: cc-by-sa-4.0

CrossEncoder for Slovene NLI

The model was trained using the SentenceTransformers CrossEncoder class.
It is based on SloBerta, a monolingual Slovene model.

Training

This model was trained on the SI-NLI dataset.
More details and the training script are available here: repo

Performance

The model achieves the following metrics:

Test accuracy: 75.95
Dev accuracy: 75.14

Usage

The model can be used for inference using the below code:

from sentence_transformers import CrossEncoder

model = CrossEncoder('jacinthes/cross-encoder-sloberta-si-nli')
premise = 'Pojdi z menoj v toplice.'
hypothesis = 'Bova lepa bova fit.'
prediction = model.predict([premise, hypothesis])
int2label = {0: 'entailment', 1: 'neutral', 2:'contradiction'}
print(int2label[prediction.argmax()])