Learning Rate Schedules
Linear Warmup With Linear Decay
Linear Warmup With Linear Decay is a learning rate schedule in which we increase the learning rate linearly for $n$ updates and then linearly decay afterwards.
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Retrieval | 124 | 13.25% |
| Language Modelling | 96 | 10.26% |
| Question Answering | 63 | 6.73% |
| Large Language Model | 39 | 4.17% |
| Sentence | 29 | 3.10% |
| Text Classification | 28 | 2.99% |
| Sentiment Analysis | 26 | 2.78% |
| Information Retrieval | 24 | 2.56% |
| Text Generation | 22 | 2.35% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
