Datasets:
Upload README.md with huggingface_hub
Browse files
README.md
CHANGED
|
@@ -18,6 +18,8 @@ size_categories:
|
|
| 18 |
|
| 19 |
We present GIFT-Eval, a benchmark designed to advance zero-shot time series forecasting by facilitating evaluation across diverse datasets. GIFT-Eval includes 23 datasets covering 144,000 time series and 177 million data points, with data spanning seven domains, 10 frequencies, and a range of forecast lengths. This benchmark aims to set a new standard, guiding future innovations in time series foundation models.
|
| 20 |
|
|
|
|
|
|
|
| 21 |
[📄 Paper](https://arxiv.org/abs/2410.10393)
|
| 22 |
|
| 23 |
[🖥️ Code](https://github.com/SalesforceAIResearch/gift-eval)
|
|
|
|
| 18 |
|
| 19 |
We present GIFT-Eval, a benchmark designed to advance zero-shot time series forecasting by facilitating evaluation across diverse datasets. GIFT-Eval includes 23 datasets covering 144,000 time series and 177 million data points, with data spanning seven domains, 10 frequencies, and a range of forecast lengths. This benchmark aims to set a new standard, guiding future innovations in time series foundation models.
|
| 20 |
|
| 21 |
+
To facilitate the effective pretraining and evaluation of foundation models, we also provide a non-leaking pretraining dataset --> [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain).
|
| 22 |
+
|
| 23 |
[📄 Paper](https://arxiv.org/abs/2410.10393)
|
| 24 |
|
| 25 |
[🖥️ Code](https://github.com/SalesforceAIResearch/gift-eval)
|