Update README.md

README.md

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 Memorial Health Library : https://www.memorial.com.tr/saglik-kutuphanesi
 
-- **Repository:** [More Information Needed]
 
 ## Uses
 
@@ -30,13 +29,6 @@ Memorial Health Library : https://www.memorial.com.tr/saglik-kutuphanesi
 
 <!-- This section describes suitable use cases for the dataset. -->
 
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
-
-[More Information Needed]
 
 ## Dataset Structure
 
@@ -54,31 +46,27 @@ Memorial Health Library : https://www.memorial.com.tr/saglik-kutuphanesi
 ## Dataset Creation
 
 ### Curation Rationale
-This dataset was created to increase the Turkish medical data in HuggingFace Datasets library.
-
 <!-- Motivation for the creation of this dataset. -->
+This dataset was created to increase the Turkish medical text data in HuggingFace Datasets library.
+
 
 ### Source Data
+<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
 Memorial is a hospital network based in Turkey. Their website provides a health library, which the contents were written by doctors who are experts in their fields.
 
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
 
 #### Data Collection and Processing
-The contents were scraped using Python's BeautifulSoup library.
 <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
+The contents were scraped using Python's BeautifulSoup library.
 
 ### Annotations
-Each text in the dataset was tokenized and counted afterwards.
-
 <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
+Each text in the dataset was tokenized and counted afterwards.
+Total Number of Tokens : 5227389
 
 #### Annotation process
-Tokenization was done using Tiktoken's encoding `cl100k_base`, used by `gpt-4-turbo`, `gpt-4`, `gpt-3.5-turbo`, etc.
-
 <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
-
-[More Information Needed]
-
+Tokenization was done using Tiktoken's encoding `cl100k_base`, used by `gpt-4-turbo`, `gpt-4`, `gpt-3.5-turbo`, etc.
 
 #### Personal and Sensitive Information
 This data does not contain ant personal, sensitive or private information.