hitenvk22/finstream-sentiment

FinStream financial sentiment classifier fine-tuned on Financial PhraseBank.
Part of the FinStream Active Learning Pipeline.

Model Description

Property	Value
Base model	distilroberta-base
Task	3-class financial sentiment classification
Dataset	Financial PhraseBank (~4,845 sentences)
Labels	negative (Bearish) · neutral · positive (Bullish)
Accuracy	0.8443298969072165
F1 macro	0.8457725376192002
Precision	0.8510783764659424
Recall	0.8443298969072165
Training hardware	Kaggle T4 GPU · FP16 · 5 epochs

Quick Start

from transformers import pipeline

classifier = pipeline(
    "text-classification",
    model="hitenvk22/finstream-sentiment",
    tokenizer="hitenvk22/finstream-sentiment",
)

result = classifier("The company reported record earnings, beating all analyst estimates.")
print(result)
# [{'label': 'positive', 'score': 0.96}]

Label Mapping

Integer	Label	Financial meaning
0	negative	Bearish — price likely to fall
1	neutral	No directional signal
2	positive	Bullish — price likely to rise

Intended Use

• Real-time financial news sentiment scoring
• Portfolio risk alerts
• Market signal generation
• Active learning pipeline retraining target

Limitations

• Trained on English-only text
• Short sentences (< 128 tokens); may underperform on long documents
• Not fine-tuned on post-2020 financial language

Training Details

• Optimiser: AdamW · LR 2e-5 · warmup 10 % · weight decay 0.01
• Early stopping patience: 2 epochs
• Dynamic padding via DataCollatorWithPadding