--- language: - en license: apache-2.0 library_name: transformers tags: - text-classification - bert - finbert - finance - sentiment - sentiment-analysis - financial-sentiment datasets: - FinanceInc/auditor_sentiment - nickmuchi/financial-classification - warwickai/financial_phrasebank_mirror pipeline_tag: text-classification --- # 🎯 FinBERT-Pro An improved financial sentiment model built on [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert). Fine-tuned on 3 expert-annotated financial datasets for more robust sentiment classification. The model provides softmax outputs for three sentiment classes: **Positive**, **Negative**, **Neutral**. ## 🚀 Usage ```python from transformers import pipeline classifier = pipeline("text-classification", model="ENTUM-AI/FinBERT-Pro") classifier("Stock price soars on record-breaking earnings report") # [{'label': 'Positive', 'score': 0.99}] classifier("Company announces quarterly earnings results") # [{'label': 'Neutral', 'score': 0.98}] classifier("Revenue decline signals weakening market position") # [{'label': 'Negative', 'score': 0.98}] ``` ## 📊 Training Data Fine-tuned on 3 expert-annotated public datasets: | Dataset | Samples | |---------|---------| | [FinanceInc/auditor_sentiment](https://huggingface.co/datasets/FinanceInc/auditor_sentiment) | ~4.8K | | [nickmuchi/financial-classification](https://huggingface.co/datasets/nickmuchi/financial-classification) | ~5K | | [warwickai/financial_phrasebank_mirror](https://huggingface.co/datasets/warwickai/financial_phrasebank_mirror) | ~4.8K | Unlike the original FinBERT (trained on a single dataset), FinBERT-Pro combines multiple expert-annotated sources for better generalization across different financial text styles. ## 🔍 What's Different from FinBERT? - **Multiple data sources** — trained on 3 expert-annotated datasets instead of 1 - **Class-weighted training** — handles imbalanced label distributions - **Better generalization** — diverse training data improves robustness on unseen financial texts ## ⚠️ Limitations - English only - Designed for short financial texts (headlines, news, reports)