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.