finetuning-sentiment-model-for-c2er
teomotun/finetuning-sentiment-model-for-c2er
Tracked by OpenModelStats since September 14, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 3,058
- Total downloadsCumulative all-time download counter reported by the source platform.
- 101.6K
- Gained 7DIncrease in cumulative total downloads between OpenModelStats' own observations seven days apart.
- +752(increase)
- 0.8%(up) vs baseline
- Gained 30DIncrease in cumulative total downloads between OpenModelStats' own observations roughly thirty days apart.
- —
- LikesCommunity likes reported by the source platform.
- 0
- +0 in 7D
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #403 among tracked Text Classification models.
- #15,072
- 44(up 44 places)this week
- Parameters
- —
- Last source update
- Oct 21, 2022
- MomentumOpenModelStats' composite rising-model signal (0–100): a percentile blend of absolute 7-day download gains, capped percentage growth, and likes gained. See Methodology.
- 50.2
- finetuning-sentiment-model-for-c2er gained 752 downloads during the last seven tracked days.
- It moved from #402 to #403 among tracked Text Classification models this week.
Downloads over time
Cumulative total downloads observed by OpenModelStatsLikes over time
Rank among tracked models
Lower is betterOverview
finetuning-sentiment-model-for-c2er is a text classification model published by teomotun. OpenModelStats has tracked the model since Sep 14, 2026, most recently observing it Sep 21, 2026.
- Published
- Oct 20, 2022
- Last updated
- Oct 21, 2022
- Library
- transformers
- License
- apache-2.0
- Task
- Text Classification
- Parameters
- —
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
- 107
transformerspytorchtensorboarddistilberttext-classificationgenerated_from_trainerlicense:apache-2.0text-embeddings-inferenceendpoints_compatibleregion:usdeploy:azure
Publisher
teomotunView publisher statistics →Similar models
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