FinBERT-FedAvg

FinBERT–FedAvg: Federated Averaging for Financial Sentiment Analysis

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📌 Model Summary

This model is a federated version of FinBERT fine-tuned for financial sentiment classification (Positive / Negative / Neutral).

Training is performed across three clients:

• Financial Twitter posts
• Financial news headlines
• Financial reports & statements

This model is trained using the Federated Averaging (FedAvg) algorithm, where each client trains locally on its own data and only model weights are shared. No raw data is exchanged, supporting privacy-preserving learning.

This model is part of a research project comparing:

• FedAvg
• FedProx
• Adaptive Aggregation

for federated financial NLP.

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🧠 Intended Use

Designed for:

• Financial sentiment research
• Risk & market analytics
• Academic exploration of federated learning

Not intended for automated trading without expert oversight.

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🏗 Model Architecture

Base Model:

ProsusAI/finbert

Task:

Sequence classification — 3 classes

Training Setup:

3 federation clients
10 global rounds
3 local epochs
FedAvg aggregation

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📊 Client Data Sources

No raw data is shared between clients.

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🔐 Privacy Advantage

Only model updates are exchanged — not text data.
This supports data governance and privacy-aware ML.

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📈 Performance (Validation)

FedAvg provided strong and stable global performance across heterogeneous financial text sources.

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🚀 Example Usage

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

model = AutoModelForSequenceClassification.from_pretrained(
    "harshprasad03/FinBERT-FedAvg"
)
tokenizer = AutoTokenizer.from_pretrained(
    "harshprasad03/FinBERT-FedAvg"
)

text = "Tech stocks fell after negative earnings guidance."

inputs = tokenizer(text, return_tensors="pt")
outputs = model(**inputs)

prob = torch.softmax(outputs.logits, dim=1)
print(prob)

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⚠️ Limitations

• Trained only on finance-domain text
• Sentiment ≠ market prediction
• Model may inherit dataset biases
• Designed for research use

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📚 Citation

Harsh Prasad, Sai Dhole (2025).
FedAvg-based Federated FinBERT for Financial Sentiment Analysis.

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👨‍💻 Authors

Harsh Prasad AI and ML Research

Sai Dhole AI and ML Research

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