RRepoGEO

REPOGEO REPORT · LITE

ProsusAI/finBERT

Default branch master · commit 44995e0c · scanned 6/29/2026, 11:37:57 AM

GitHub: 2,167 stars · 530 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
81 /100
Healthy
Category recall
2 / 2
Avg rank #1.0 when recommended
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 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 specific topics to the repository

    Why:

    COPY-PASTE FIX
    ['financial-nlp', 'sentiment-analysis', 'bert', 'huggingface', 'finance', 'nlp', 'deep-learning']
  • mediumreadme#2
    Refine the README's opening paragraph to highlight specialization

    Why:

    CURRENT
    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 is a specialized pre-trained NLP model for financial sentiment analysis, built by further training the BERT language model on a large financial corpus. Unlike generic BERT models, FinBERT is fine-tuned to understand the unique nuances of financial text, making it highly effective for tasks like analyzing financial news and reports. The FinBERT sentiment analysis model is available on the Hugging Face model hub.
  • mediumhomepage#3
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    https://huggingface.co/ProsusAI/finbert

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
2 / 2
100% of queries surface ProsusAI/finBERT
Avg rank
#1.0
Lower is better. #1 = top recommendation.
Share of voice
20%
Of all named tools, what % are you?
Top rival
RoBERTa
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. RoBERTa · recommended 1×
  2. DistilBERT · recommended 1×
  3. XLNet · recommended 1×
  4. BERT · recommended 1×
  5. BERT-base-uncased · recommended 1×
  • CATEGORY QUERY
    What are effective NLP models for sentiment analysis of financial news and reports?
    you: #1
    AI recommended (in order):
    1. FinBERT ← you
    2. RoBERTa
    3. DistilBERT
    4. XLNet
    5. BERT
    Show full AI answer
  • CATEGORY QUERY
    Which pre-trained language models excel at financial sentiment classification tasks?
    you: #1
    AI recommended (in order):
    1. FinBERT ← you
    2. BERT-base-uncased
    3. RoBERTa-base
    4. DistilBERT-base-uncased
    5. XLNet-base-cased
    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 did not name ProsusAI/finBERT — likely talking about a different project

    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?

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MARKDOWN (README)
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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
ProsusAI/finBERT — RepoGEO report