indobertweet-base-Indonesian-sentiment-analysis
Aardiiiiy/indobertweet-base-Indonesian-sentiment-analysis
Tracked by OpenModelStats since September 4, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 1,869
- Total downloadsCumulative all-time download counter reported by the source platform.
- 63K
- Gained 7DIncrease in cumulative total downloads between OpenModelStats' own observations seven days apart.
- +679(increase)
- 1.1%(up) vs baseline
- Gained 30DIncrease in cumulative total downloads between OpenModelStats' own observations roughly thirty days apart.
- —
- LikesCommunity likes reported by the source platform.
- 8
- +0 in 7D
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #549 among tracked Text Classification models.
- #22,914
- 337(down 337 places)this week
- Parameters
- 111M
- Last source update
- May 23, 2025
- MomentumOpenModelStats' composite rising-model signal (0–100): a percentile blend of absolute 7-day download gains, capped percentage growth, and likes gained. See Methodology.
- 50.9
- indobertweet-base-Indonesian-sentiment-analysis gained 679 downloads during the last seven tracked days.
- It moved from #542 to #549 among tracked Text Classification models this week.
Downloads over time
Daily gain between consecutive observationsLikes over time
Rank among tracked models
Lower is betterOverview
indobertweet-base-Indonesian-sentiment-analysis is a text classification model published by Aardiiiiy. OpenModelStats has tracked the model since Sep 4, 2026, most recently observing it Oct 3, 2026.
- Published
- Aug 4, 2024
- Last updated
- May 23, 2025
- Library
- transformers
- License
- mit
- Task
- Text Classification
- Parameters
- 110,560,515
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
- 97
transformerssafetensorsberttext-classificationiddoi:10.57967/hf/5111license:mitendpoints_compatibleregion:usdeploy:azure
Publisher
AardiiiiyView publisher statistics →Similar models
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