Finbert-Tone, an open-source financial tweet topic classification model, supports accurate classification of 20 financial topics for financial tweets.

Finbert Tone Finetuned Finance Topic Classification

Developed by nickmuchi

A financial tweet topic classification model fine-tuned on the Twitter financial news topic dataset, supporting 20 types of financial topic classifications.

Text Classification

Transformers

#Financial tweet classification #Multi-topic recognition #Imbalanced data optimization

Downloads 2,813

Release Time : 12/30/2022

Model Overview

This model is used for topic classification of financial-related tweets, covering 20 different topics. Weight adjustment has been made for the problem of uneven distribution of category labels to improve the overall performance.

Model Features

Multi-topic classification

Capable of classifying given tweets into 20 different financial topics.

Performance optimization

Adjust weights for the problem of uneven distribution of category labels, pay more attention to labels with fewer samples, and improve the overall performance.

Model Capabilities

Financial text classification

Tweet topic recognition

Multi-label classification

Use Cases

Financial information analysis

Financial news classification

Automatically classify the topics of financial-related tweets

Accuracy: 91.06%, F1 score: 91.06%

Market sentiment analysis

Identify the financial topics discussed in tweets to assist in market sentiment analysis

🚀 finbert-tone-finetuned-finance-topic-classification

This model is a fine - tuned version of [yiyanghkust/finbert - tone](https://huggingface.co/yiyanghkust/finbert - tone) on the [Twitter Financial News Topic](https://huggingface.co/datasets/zeroshot/twitter - financial - news - topic) dataset, which can classify financial topics of tweets.

🚀 Quick Start

This model is a fine - tuned version of [yiyanghkust/finbert - tone](https://huggingface.co/yiyanghkust/finbert - tone) on [Twitter Financial News Topic](https://huggingface.co/datasets/zeroshot/twitter - financial - news - topic) dataset. It achieves the following results on the evaluation set:

Loss: 0.509021
Accuracy: 0.910615
F1: 0.910647
Precision: 0.911335
Recall: 0.910615

✨ Features

The model determines the financial topic of given tweets over 20 various topics.
Given the unbalanced distribution of the class labels, the weights were adjusted to pay attention to the less sampled labels which should increase overall performance.

🔧 Technical Details

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e - 05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon = 1e - 08
lr_scheduler_type: linear
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
No log	1.0	266	0.5152	0.8552	0.8504	0.8508	0.8552
0.7618	2.0	532	0.3999	0.8790	0.8781	0.8842	0.8790
0.7618	3.0	798	0.3628	0.8943	0.8940	0.8958	0.8943
0.16	4.0	1064	0.3776	0.8997	0.9001	0.9025	0.8997
0.16	5.0	1330	0.4286	0.8999	0.9002	0.9022	0.8999
0.058	6.0	1596	0.4500	0.9043	0.9042	0.9055	0.9043
0.058	7.0	1862	0.4689	0.9021	0.9017	0.9026	0.9021
0.0267	8.0	2128	0.4918	0.9031	0.9029	0.9039	0.9031
0.0267	9.0	2394	0.5030	0.9048	0.9049	0.9060	0.9048
0.0177	10.0	2660	0.5052	0.9033	0.9034	0.9044	0.9033
0.0177	11.0	2926	0.5265	0.9036	0.9034	0.9055	0.9036
0.013	12.0	3192	0.5267	0.9041	0.9041	0.9058	0.9041
0.013	13.0	3458	0.5090	0.9106	0.9106	0.9113	0.9106
0.0105	14.0	3724	0.5315	0.9067	0.9067	0.9080	0.9067
0.0105	15.0	3990	0.5339	0.9084	0.9084	0.9093	0.9084
0.0068	16.0	4256	0.5414	0.9072	0.9074	0.9088	0.9072
0.0051	17.0	4522	0.5460	0.9092	0.9091	0.9102	0.9092
0.0051	18.0	4788	0.5438	0.9072	0.9073	0.9081	0.9072
0.0035	19.0	5054	0.5474	0.9072	0.9073	0.9080	0.9072
0.0035	20.0	5320	0.5484	0.9079	0.9080	0.9087	0.9079

Framework versions

Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.8.0
Tokenizers 0.13.2

📚 Documentation

Property	Details
Tags	generated_from_trainer, twitter - financial - topic - classification, financial, stocks, twitter

Datasets

Property	Details
Datasets	zeroshot/twitter - financial - news - topic

Metrics

Property	Details
Metrics	F1, accuracy, precision, recall

Model Index

Property	Details
Model Name	finbert - tone - finetuned - finance - topic - classification
Task	Text Classification (text - classification)
Dataset Name	twitter - financial - news - topic
Dataset Type	finance
F1	0.910647
Accuracy	0.910615

Widget Examples

Example Title	Text
Analyst Update	Here are Thursday's biggest analyst calls: Apple, Amazon, Tesla, Palantir, DocuSign, Exxon & more
Fed \| Central Banks	LIVE: ECB surprises with 50bps hike, ending its negative rate era. President Christine Lagarde is taking questions
Company \| Product News	Goldman Sachs traders countered the industry’s underwriting slump with revenue gains that raced past analysts’ estimates. The trading operation posted a 32% surge in second - quarter revenue that included another banner period for fixed income
Treasuries \| Corporate Debt	China Evergrande Group’s onshore bond holders rejected a plan by the distressed developer to further extend a bond payment which was due on Friday. Rebecca Choong Wilkins reports on Bloomberg Television
Dividend	Investing Club: Morgan Stanley's dividend, buyback pay us for our patience after quarterly missteps
Earnings	Investing Club: Our takes on Amazon and Apple heading into next week's earnings reports
Energy \| Oil	JUST RELEASED: Oil Price Dynamics Report → Over the past week, oil prices decreased as supply expectations rose and anticipated demand remained unchanged.
Financials	Delta Air Lines fell short of profit expectations in the second quarter and said high operating costs will persist through the rest of the year. Bloomberg Opinion's Brooke Sutherland has more on 'Bloomberg Markets'
Currencies	BREAKING: The Indian rupee plummets to a record 80 per US dollar as foreign investors pull out money from the nation's stocks
General News \| Opinion	Twitter and Elon Musk are now in a high stakes/high risk situation, one analyst said.
Gold \| Metals \| Materials	Copper prices are signaling that investors are bearish on the economy, strategist says
IPO	Johnson & Johnson CFO Joe Wolk says the company is positioned for the long term and the plans for its consumer operations include an IPO. He speaks on 'Bloomberg Markets'
Legal \| Regulation	Company and Elon Musk are set for a blockbuster courtroom battle over Musk’s attempt to terminate his $44 billion acquisition deal for $TWTR, according to Wedbush analyst Dan Ives.
M&A \| Investments	Amazon to buy primary health care provider One Medical for roughly $3.9 billion
Macro	Barclays Senior Analyst For Equity Research Jason Goldberg: 'Price expectations have changed.'' The global markets business recorded $6.47 billion of revenue in the quarter with rates, commodities and currencies helping drive the fixed - income gains.
Markets	US stocks push higher in a volatile session. We break it down on The Countdown to The Close
Politics	Zelenskyy fires security chiefs over ‘treasonous’ officials
Personnel Change	Airbnb co - founder Joe Gebbia is stepping down
Stock Commentary	French power group EDF requests its shares be suspended
Stock Movement	JUST IN: Alibaba shares slide as much as 5.7%, bringing this week's slump to over 15%, after it reportedly faced a data - theft inquiry

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