{"url":"/dataset/etth1-192","name":"ETTh1 (192)","full_name":"Electricity Transformer Temperature","description_markdown":"The **Electricity Transformer Temperature** (**ETT**) is a crucial indicator in the electric power long-term deployment. This dataset consists of 2 years data from two separated counties in China. To explore the granularity on the Long sequence time-series forecasting (LSTF) problem, different subsets are created, {ETTh1, ETTh2} for 1-hour-level and ETTm1 for 15-minutes-level. Each data point consists of the target value ”oil temperature” and 6 power load features. The train/val/test is 12/4/4 months.\r\n\r\nSource: [https://arxiv.org/pdf/2012.07436.pdf](https://arxiv.org/pdf/2012.07436.pdf)\r\nImage Source: [https://github.com/zhouhaoyi/ETDataset](https://github.com/zhouhaoyi/ETDataset)","description_withheld":null,"homepage":"https://github.com/zhouhaoyi/ETDataset","introduced_date":"2020-12-14","introduced_date_note":null,"introduced_by":{"paper":"/paper/informer-beyond-efficient-transformer-for","title":"Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting","first_author":"Haoyi Zhou","url":null},"license":null,"modalities":[],"tasks":[{"name":"GLinear","url":"/task/glinear","datasets_with_task":"/datasets/task/glinear"}],"languages":[],"variants":["ETTh1 (192)"],"data_loaders":[],"num_papers_in_archive":8,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/glinear-on-etth1-192","task":"GLinear","dataset_variant":"ETTh1 (192)","rows":1,"metrics":["MSE"],"first_row_in_archive_order":{"model":"GLinear","paper":"/paper/bridging-simplicity-and-sophistication-using-1","metrics":{"MSE":"0.4202"},"code_links":[{"title":"t-rizvi/GLinear","url":"https://github.com/t-rizvi/GLinear"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/bridging-simplicity-and-sophistication-using-1","title":"Bridging Simplicity and Sophistication using GLinear: A Novel Architecture for Enhanced Time Series Prediction","date":"2025-01-02","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}