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finbert-sentiment
leplebi/finbert-sentiment
finbert-sentiment is a text classification model from leplebi. Use it when you need a label for a piece of text. The card lists the license as other.
A fine-tuned version of distilbert/distilbert-base-uncased for financial text sentiment classification (negative / neutral / positive).
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At a glance
- Task
- Text Classification
- License
- other
- Model type
- distilbert
- Access
- Public
- Created
- Jul 4, 2026
- Updated
- Jul 4, 2026
- SHA
- e5f0e333
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Model card
From the Hugging Face model README
finbert-sentiment-tr
A fine-tuned version of distilbert/distilbert-base-uncased for financial
text sentiment classification (negative / neutral / positive).
Usage
```python from transformers import pipeline
classifier = pipeline("text-classification", model="leplebi/finbert-sentiment-tr", top_k=None) classifier("The company reported strong quarterly earnings.") ```
Training Details
- Base model: distilbert/distilbert-base-uncased
- Dataset: Financial PhraseBank (Malo et al., 2014), "50Agree" configuration (~4846 sentences)
- Epochs: 4 (best checkpoint selected at epoch 3, based on
f1_macro) - Learning rate: 2e-5
- Batch size: 16
Results (test set, 727 examples)
| Metric | Value |
|---|---|
| Accuracy | 0.8638 |
| F1 Macro | 0.8497 |
| F1 Weighted | 0.8636 |
| Precision Macro | 0.8372 |
| Recall Macro | 0.8675 |
Limitations
- Trained on short, single-sentence financial statements; performance on longer reports or paragraphs may differ.
- Not intended for use on non-English text.
License / Data Source Note
This model was trained using the Financial PhraseBank dataset (Malo et al., 2014), which is distributed under an academic/research license. Please review the original license terms before any commercial use.
- Task
- Text Classification
- Type
- distilbert
- License
- other
- Languages
- en
- Created
- Jul 4, 2026
- Updated
- Jul 4, 2026