tobacco-small-3482 is a state-of-the-art machine learning benchmark indexed on Codesota. This page tracks published model results, top scores per metric, and the SOTA timeline for tobacco-small-3482.
Accuracy is the reported evaluation metric for tobacco-small-3482. Codesota tracks published model scores on this metric so readers can compare state-of-the-art results across sources and model families.
Higher is better
| Rank | Model | Trust | Score | Year | Links | Fix |
|---|---|---|---|---|---|---|
| 01 | Optimized Text CNN | verified | 84 | 2020 | Paper ↗Code ↗ | Looks wrong? |
| 02 | Lightweight TextCNN with Dual Optimizer | verified | 83 | 2020 | Paper ↗Code ↗ | Looks wrong? |
| 03 | Lightweight Text CNN | verified | 82.5 | 2020 | Paper ↗Code ↗ | Looks wrong? |
Training Time Min is the reported evaluation metric for tobacco-small-3482. Codesota tracks published model scores on this metric so readers can compare state-of-the-art results across sources and model families.
Higher is better
| Rank | Model | Trust | Score | Year | Links | Fix |
|---|---|---|---|---|---|---|
| 01 | Optimized Text CNN | verified | 9.00 | 2020 | Paper ↗Code ↗ | Looks wrong? |
| 02 | Lightweight Text CNN | verified | 5.00 | 2020 | Paper ↗Code ↗ | Looks wrong? |
| 03 | Lightweight TextCNN with Dual Optimizer | verified | 2.00 | 2020 | Paper ↗Code ↗ | Looks wrong? |