RRepoGEO

REPOGEO REPORT · LITE

davidtvs/pytorch-lr-finder

Default branch master · commit 76df3050 · scanned 6/28/2026, 3:06:47 PM

GitHub: 1,007 stars · 121 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 davidtvs/pytorch-lr-finder, 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
  • highabout#1
    Update the 'About' description to emphasize its standalone utility

    Why:

    CURRENT
    A learning rate range test implementation in PyTorch
    COPY-PASTE FIX
    A dedicated, standalone PyTorch utility for implementing Leslie Smith's learning rate range test to find optimal learning rates.
  • hightopics#2
    Add more specific topics to improve categorization and query matching

    Why:

    CURRENT
    learning-rate, pytorch
    COPY-PASTE FIX
    learning-rate, pytorch, deep-learning, neural-networks, lr-finder, machine-learning, optimization, training
  • mediumhomepage#3
    Add a homepage URL to complete repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/davidtvs/pytorch-lr-finder

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 davidtvs/pytorch-lr-finder
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
fastai
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. fastai · recommended 2×
  2. torch_lr_finder · recommended 1×
  3. torch.optim.lr_scheduler.CyclicLR · recommended 1×
  4. torch.optim.lr_scheduler.OneCycleLR · recommended 1×
  5. torch.optim.lr_scheduler.ReduceLROnPlateau · recommended 1×
  • CATEGORY QUERY
    How can I effectively determine an optimal learning rate for my PyTorch model training?
    you: not recommended
    AI recommended (in order):
    1. fastai
    2. torch_lr_finder
    3. torch.optim.lr_scheduler.CyclicLR
    4. torch.optim.lr_scheduler.OneCycleLR
    5. torch.optim.lr_scheduler.ReduceLROnPlateau
    6. torch.optim.lr_scheduler.CosineAnnealingLR
    7. torch.optim.lr_scheduler.ExponentialLR
    8. StepLR
    9. Optuna
    10. Ray Tune
    11. torchvision.models
    12. Hugging Face Transformers

    AI recommended 12 alternatives but never named davidtvs/pytorch-lr-finder. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are some good PyTorch libraries for performing a learning rate range test?
    you: not recommended
    AI recommended (in order):
    1. PyTorch Lightning
    2. fastai
    3. pytorch_lr_finder
    4. Ignite
    5. Catalyst

    AI recommended 5 alternatives but never named davidtvs/pytorch-lr-finder. 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 davidtvs/pytorch-lr-finder?
    pass
    AI named davidtvs/pytorch-lr-finder explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts davidtvs/pytorch-lr-finder in production, what risks or prerequisites should they evaluate first?
    pass
    AI named davidtvs/pytorch-lr-finder 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 davidtvs/pytorch-lr-finder solve, and who is the primary audience?
    pass
    AI named davidtvs/pytorch-lr-finder explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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davidtvs/pytorch-lr-finder — 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