Update README.md

README.md

@@ -17,7 +17,7 @@ pretty_name: naab (A ready-to-use plug-and-play corpus in Farsi)
 ---
 
 # naab: A ready-to-use plug-and-play corpus in Farsi
-_[If you wanted to join our community to keep up with news, models and datasets from naab, click on [this](https://docs.google.com/forms/d/e/1FAIpQLSe8kevFl_ODCx-zapAuOIAQYr8IvkVVaVHOuhRL9Ha0RVJ6kg/viewform) link.]_
+_[If you want to join our community to keep up with news, models and datasets from naab, click on [this](https://docs.google.com/forms/d/e/1FAIpQLSe8kevFl_ODCx-zapAuOIAQYr8IvkVVaVHOuhRL9Ha0RVJ6kg/viewform) link.]_
 
 ## Table of Contents
 - [Dataset Card Creation Guide](#dataset-card-creation-guide)
@@ -67,7 +67,7 @@ dataset = load_dataset("SLPL/naab", split="train[:10%]")
 
 ### Supported Tasks and Leaderboards
 
-This corpus can be used for training all language models which can be trained by mask language modeling.
+This corpus can be used for training all language models which can be trained by Masked Language Modeling (MLM) or any other self-supervised objective.
 
 - `language-modeling`
 - `masked-language-modeling`
@@ -85,7 +85,7 @@ Each row of the dataset will look like something like the below:
 
 ### Data Splits
 
-This dataset includes two splits (`train` and `test`). We split these two by dividing the randomly permuted version of the corpus into (95%, 5%) division respected to (`train`, `test`). Since `validation` is usually occurring during the train with the `train` dataset we avoid proposing another split for it.
+This dataset includes two splits (`train` and `test`). We split these two by dividing the randomly permuted version of the corpus into (95%, 5%) division respected to (`train`, `test`). Since `validation` is usually occurring during training with the `train` dataset we avoid proposing another split for it.
 
 |                         | train | test |
 |-------------------------|------:|-----:|
@@ -150,7 +150,7 @@ We used a preprocessor based on some stream-based Linux kernel commands so that
 
 Since this corpus is briefly a compilation of some former corpora we take no responsibility for personal information included in this corpus. If you detect any of these violations please let us know, we try our best to remove them from the corpus ASAP.
 
-We tried our best to provide anonymously while keeping the crucial information. We shuffled some parts of the corpus so the information passing through possible conversations wouldn't be harmful. 
+We tried our best to provide anonymity while keeping the crucial information. We shuffled some parts of the corpus so the information passing through possible conversations wouldn't be harmful. 
 
 ## Additional Information