Update README.md

README.md

@@ -71,25 +71,25 @@ The label2id dictionary can be found at [here](https://huggingface.co/datasets/t
 ### Data Splits
 
 
-| split                     | number of texts | description |
-|:--------------------------|-----:|:-----|
-| test                      | 1679 | alias of `temporal_2021_test` |
-| train                     | 4585 | alias of `temporal_2020_train` | 
-| validation                |  573 | alias of `temporal_2020_validation` |
-| temporal_2020_test        |  573 | test set in 2020 period of temporal split |
-| temporal_2021_test        | 1679 | test set in 2021 period of temporal split |
-| temporal_2020_train       | 4585 | training set in 2020 period of temporal split |
-| temporal_2021_train       | 1505 | training set in 2021 period of temporal split |
-| temporal_2020_validation  |  573 | validation set in 2020 period of temporal split |
-| temporal_2021_validation  |  188 | validation set in 2021 period of temporal split |
-| random_train              | 4564 | training set of random split (mix of 2020 and 2021) |
-| random_validation         |  573 | validation set of random split (mix of 2020 and 2021) |
-| coling2022_random_test    | 5536 | test set of random split used in COLING 2022 Tweet Topic paper |
-| coling2022_random_train   | 5731 | training set of random split used in COLING 2022 Tweet Topic paper |
-| 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|
-
-For the temporal-shift setting, we recommend to train models on `train` (`temporal_2020_train`) with `validation` (`temporal_2020_validation`) and evaluate on `test` (`temporal_2021_test`).
+| split                       | number of texts | description |
+|:----------------------------|-----:|:-----|
+| `test`                      | 1679 | alias of `temporal_2021_test` |
+| `train`                     | 4585 | alias of `temporal_2020_train` | 
+| `validation`                |  573 | alias of `temporal_2020_validation` |
+| `temporal_2020_test`        |  573 | test set in 2020 period of temporal split |
+| `temporal_2021_test`        | 1679 | test set in 2021 period of temporal split |
+| `temporal_2020_train`       | 4585 | training set in 2020 period of temporal split |
+| `temporal_2021_train`       | 1505 | training set in 2021 period of temporal split |
+| `temporal_2020_validation`  |  573 | validation set in 2020 period of temporal split |
+| `temporal_2021_validation`  |  188 | validation set in 2021 period of temporal split |
+| `random_train`              | 4564 | training set of random split (mix of 2020 and 2021) |
+| `random_validation`         |  573 | validation set of random split (mix of 2020 and 2021) |
+| `coling2022_random_test`    | 5536 | test set of random split used in COLING 2022 Tweet Topic paper |
+| `coling2022_random_train`   | 5731 | training set of random split used in COLING 2022 Tweet Topic paper |
+| `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|
+
+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`).
 To get a result that is comparable with the results of the COLING 2022 Tweet Topic paper, please use `coling2022_temporal_train` and `coling2022_temporal_test` for temporal-shift, and `coling2022_random_train` and `coling2022_temporal_test` fir random split (note that the coling2022 split does not have validation set).