Update README.md

README.md

@@ -89,6 +89,22 @@ The label2id dictionary can be found at [here](https://huggingface.co/datasets/t
 | `coling2022_temporal_test`  | 5536 | test set of temporal split used in COLING 2022 Tweet Topic paper |
 | `coling2022_temporal_train` | 5731 | training set of temporal split used in COLING 2022 Tweet Topic paper|
 
+| split                   | number of texts | description |
+|:------------------------|-----:|------:|
+| test_2020               |  573 | test dataset from September 2019 to August 2020 |
+| test_2021               | 1679 | test dataset from September 2020 to August 2021 |
+| train_2020              | 4585 | training dataset from September 2019 to August 2020 |
+| train_2021              | 1505 | training dataset from September 2020 to August 2021 |
+| train_all               | 6090 | combined training dataset of `train_2020` and `train_2021` |
+| validation_2020         |  573 | validation dataset from September 2019 to August 2020 |
+| validation_2021         |  188 | validation dataset from September 2020 to August 2021 | 
+| train_random            | 4564 | randomly sampled training dataset with the same size as `train_2020` from `train_all` |
+| validation_random       |  573 | randomly sampled training dataset with the same size as `validation_2020` from `validation_all` |
+| test_coling2022_random  | 5536 | random split used in the COLING paper |
+| train_coling2022_random | 5731 | random split used in the COLING paper |
+| test_coling2022         | 5536 | temporal split used in the COLING paper |
+| train_coling2022        | 5731 | temporal split used in the COLING paper |
+
 For the temporal-shift setting, we recommend to train models on `train` (an alias of `temporal_2020_train`) with `validation` (an alias of `temporal_2020_validation`) and evaluate on `test` (an alias of `temporal_2021_test`).
 For the random split, we recommend to train models on `random_train` with `random_validation` and evaluate on `test` (`temporal_2021_test`).