FewShotIssueClassifier-NLBSE23
This is a SetFit model using Sentence Transformers to map sentences & paragraphs to a 768 dimensional dense vector space. It be used for tasks like clustering or semantic search.
This specific model is fine-tuned for Issue Report Classification in 4 classes: bug, documentation, feature, question
Usage
You can use the model like this:
from sentence_transformers.losses import CosineSimilarityLoss
from setfit import SetFitModel
from setfit import SetFitTrainer
sentences = ["error in line 20", "add method list_features"]
label_mapping = {
0 : "bug",
1 : "documentation",
2 : "feature",
3 : "question"
}
model = SetFitModel.from_pretrained('PeppoCola/FewShotIssueClassifier-NLBSE23')
predictions = model.predict(sentences)
print([label_mapping[i] for i in predictions])
Dataset
This model is trained on a subset of the NLBSE23 dataset. The sample was hand-labeled, and made available on Zenodo
Citing & Authors
@software{Colavito_Few-Shot_Learning_for_2023,
title = {{Few-Shot Learning for Issue Report Classification}},
author = {Colavito, Giuseppe and Lanubile, Filippo and Novielli, Nicole},
year = 2023,
month = 2,
url = {https://github.com/collab-uniba/Issue-Report-Classification-NLBSE2023},
version = {1.0.0}
}
@dataset{colavito_giuseppe_2023_7628150,
author = {Colavito Giuseppe and
Lanubile Filippo and
Novielli Nicole},
title = {Few-Shot Learning for Issue Report Classification},
month = feb,
year = 2023,
note = {{To use this, merge the CSV with the original
dataset (after removing duplicates on the 'id'
column)}},
publisher = {Zenodo},
doi = {10.5281/zenodo.7628150},
url = {https://doi.org/10.5281/zenodo.7628150}
}
@inproceedings{Colavito-2023,
title = {Few-Shot Learning for Issue Report Classification},
author = {Colavito, Giuseppe and Lanubile, Filippo and Novielli, Nicole},
year = 2023,
booktitle = {2nd International Workshop on Natural Language-Based Software Engineering (NLBSE)}
}
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