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absa-deberta-v3
sy12ssss/absa-deberta-v3
absa-deberta-v3 is a text classification model from sy12ssss. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
DeBERTa-v3-base fine-tuned for aspect-based sentiment analysis. Input is an (aspect, sentence) pair, output is negative, neutral or positive for that aspect.
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184M
1.7 GB on disk
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- deberta-v2
- Access
- Public
- Created
- Sep 24, 2026
- Updated
- Sep 24, 2026
- SHA
- ae74dd81
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Base models
Model card
From the Hugging Face model README
absa-deberta-v3
DeBERTa-v3-base fine-tuned for aspect-based sentiment analysis. Input is an (aspect, sentence) pair, output is negative, neutral or positive for that aspect.
Int8 quantization of this model was not usable (accuracy collapsed), so the browser demo uses absa-roberta-base.
Results (588-pair test set, split by sentence)
| Runtime | Size | Accuracy |
|---|---|---|
| PyTorch fp32 | ~500 MB | 0.8214 |
Temperature scaling: T = 1.604, ECE reduced from 0.0993 to 0.0505.
Usage
Pass the aspect as the first text and the sentence as the second (tokenizer(aspect, sentence)). Divide logits by the temperature before the softmax for calibrated confidence.
Limitations
Trained on restaurant and laptop reviews only (SemEval-2014 Task 4). The aspect must be provided.
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Languages
- en
- Created
- Sep 24, 2026
- Updated
- Sep 24, 2026