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cross-encoder-sloberta-si-nli
jacinthes/cross-encoder-sloberta-si-nli
cross-encoder-sloberta-si-nli is a text classification model from jacinthes. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as cc-by-sa-4.0.
The model was trained using the SentenceTransformers CrossEncoder class. <br / It is based on SloBerta, a monolingual Slovene model.
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- cc-by-sa-4.0
- Model type
- camembert
- Access
- Public
- Created
- Apr 19, 2023
- Updated
- Apr 20, 2023
- SHA
- 7a99f0fc
Datasets
Model card
From the Hugging Face model README
CrossEncoder for Slovene NLI
The model was trained using the SentenceTransformers CrossEncoder class. <br /> It is based on SloBerta, a monolingual Slovene model.
Training
This model was trained on the SI-NLI dataset.<br /> 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()])
- Task
- Text Classification
- Library
- transformers
- Type
- camembert
- License
- cc-by-sa-4.0
- Languages
- sl
- Created
- Apr 19, 2023
- Updated
- Apr 20, 2023