REPOGEO REPORT · LITE

ProsusAI/finBERT

Default branch master · commit 44995e0c · scanned 5/18/2026, 5:42:56 AM

GitHub: 2,128 stars · 524 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

35 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 warn · 0 fail

Objective metadata checks

AI knows your name

3 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface ProsusAI/finBERT, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

hightopics#1

Add relevant topics to the repository

Why:

COPY-PASTE FIX

["financial-nlp", "sentiment-analysis", "bert", "finance", "nlp", "pytorch", "huggingface"]

highhomepage#2
Add a homepage URL to the repository metadata
Why:
COPY-PASTE FIX
```
https://huggingface.co/ProsusAI/finbert
```

mediumreadme#3

Clarify FinBERT's specialized advantage over general NLP models in the README intro

Why:

CURRENT

# FinBERT: Financial Sentiment Analysis with BERT

FinBERT sentiment analysis model is now available on Hugging Face model hub. You can get the model here. 

FinBERT is a pre-trained NLP model to analyze sentiment of financial text. It is built by further training the BERT language model in the finance domain, using a large financial corpus and thereby fine-tuning it for financial sentiment classification. For the details, please see FinBERT: Financial Sentiment Analysis with Pre-trained Language Models.

COPY-PASTE FIX

# FinBERT: The Specialized BERT Model for Financial Sentiment Analysis

FinBERT is a pre-trained NLP model specifically engineered for superior sentiment analysis in financial text, outperforming general-purpose BERT models and other generic NLP tools in this domain. It achieves this by further training the BERT language model on a large financial corpus and fine-tuning it for financial sentiment classification. The FinBERT sentiment analysis model is now available on Hugging Face model hub. You can get the model here. For technical details, please see FinBERT: Financial Sentiment Analysis with Pre-trained Language Models.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface ProsusAI/finBERT

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Hugging Face Transformers

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

Hugging Face Transformers · recommended 2×
TextBlob · recommended 2×
Google Cloud Natural Language API · recommended 1×
Amazon Comprehend · recommended 1×
OpenAI API · recommended 1×

CATEGORY QUERY
Need a tool to extract sentiment from financial reports and market news.
you: not recommended
AI recommended (in order):
1. Hugging Face Transformers
2. Google Cloud Natural Language API
3. Amazon Comprehend
4. OpenAI API
5. NLTK (Natural Language Toolkit)
6. TextBlob
AI recommended 6 alternatives but never named ProsusAI/finBERT. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Seeking a Python framework for sentiment analysis tailored for financial industry texts.
you: not recommended
AI recommended (in order):
1. Flair
2. Hugging Face Transformers
3. NLTK
4. VADER
5. TextBlob
6. spaCy
AI recommended 6 alternatives but never named ProsusAI/finBERT. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
warn
Suggestion:
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of ProsusAI/finBERT?
pass
AI named ProsusAI/finBERT explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts ProsusAI/finBERT in production, what risks or prerequisites should they evaluate first?
pass
AI named ProsusAI/finBERT explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo ProsusAI/finBERT solve, and who is the primary audience?
pass
AI named ProsusAI/finBERT explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of ProsusAI/finBERT. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/ProsusAI/finBERT.svg)](https://repogeo.com/en/r/ProsusAI/finBERT)

HTML

<a href="https://repogeo.com/en/r/ProsusAI/finBERT"><img src="https://repogeo.com/badge/ProsusAI/finBERT.svg" alt="RepoGEO" /></a>

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ProsusAI/finBERT — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite