FinSentinel — French Financial Sentiment Analysis

CamemBERT fine-tuned for financial sentiment classification.

Model Description

This model classifies financial text into 3 categories:

Bearish (negative sentiment)
Bullish (positive sentiment)
Neutral

Fine-tuned from camembert-base on 12,816 financial sentences.

Training Results

Epoch	Accuracy	F1 Score
1	70.67%	0.641
2	76.83%	0.756
3	78.00%	0.772

Test Results

Metric	Score
Accuracy	78.08%
F1 Score	0.7759

Per-class Results

Class	Precision	Recall	F1
Bearish	0.60	0.52	0.55
Bullish	0.69	0.64	0.66
Neutral	0.84	0.89	0.87

Training Details

Base model: camembert-base
Epochs: 3
Batch size: 32
Learning rate: 2e-5
Max length: 128
Train samples: 10,252
Val samples: 1,282
Test samples: 1,282

Usage

from transformers import pipeline

classifier = pipeline(
    "text-classification",
    model="Walid692/finsentinel-camembert"
)

result = classifier("La hausse des taux d'interet inquiete les investisseurs institutionnels.")
print(result)

Author

Ahmed Walid BOUANZOUL — AI Engineer GitHub: https://github.com/AhmedWalidbou/FinSentinel

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