README.md

metadata

language: en
license: apache-2.0
tags:
  - financial-nlp
  - sentiment-analysis
  - distilroberta
  - active-learning
  - transformers
datasets:
  - financial_phrasebank
metrics:
  - accuracy
  - f1
model-index:
  - name: hitenkatariya/FinStream
    results:
      - task:
          type: text-classification
        dataset:
          name: Financial PhraseBank
          type: financial_phrasebank
        metrics:
          - type: accuracy
            value: 0.868

📈 FinStream: Financial Sentiment Analysis

Fine-tuned distilroberta-base for 3-class financial sentiment classification. Part of the FinStream active learning pipeline.

Model Description

FinStream is a DistilRoBERTa-base model fine-tuned on the Financial PhraseBank dataset (sentences_allagree subset) to classify financial news into three sentiment classes:

Label	ID	Meaning
🐻 bearish	0	Negative market outlook
😐 neutral	1	No strong directional signal
🐂 bullish	2	Positive market outlook

Performance

Metric	Score
Test Accuracy	0.8680
Training Set	Financial PhraseBank (all_agree)

Usage

from transformers import pipeline

classifier = pipeline(
    'text-classification',
    model='OMCHOKSI108/FinStream',
)

result = classifier("Federal Reserve signals interest rate cuts.")
print(result)  # [{'label': 'bullish', 'score': 0.94}]

Training

• Base Model: distilroberta-base
• Dataset: Financial PhraseBank (sentences_allagree)
• Framework: Hugging Face Transformers + Trainer API
• Optimizer: AdamW with linear warmup
• Mixed Precision: FP16 (on GPU)
• Early Stopping: Patience = 3 (monitoring eval_f1)

Authors

|OM Choksi

Built as part of the FinStream Active Learning Pipeline — a portfolio-grade financial NLP project.