Update README.md

README.md

@@ -8,12 +8,12 @@ tags:
 - synthetic
 pretty_name: Password Weakness and Level Dataset
 size_categories:
-- 1M<n<10M
+- 10M<n<100M
 ---
 
 # PWLDS (Password Weakness and Level Dataset)
 
-PWLDS is a public dataset consisting of over 4 million passwords with varying assigned strength levels. The dataset was designed to help researchers, security professionals, and developers analyze password strength and build more secure systems. The dataset contains 5 classes:
+PWLDS is a public dataset of over 10 million passwords with varying assigned strength levels. The dataset was designed to help researchers, security professionals, and developers analyze password strength and build more secure systems. The dataset contains 5 classes:
 
 - `very_weak`: Represented by `0` in the dataset
 - `weak`: Represented by `1` in the dataset
@@ -23,6 +23,11 @@ PWLDS is a public dataset consisting of over 4 million passwords with varying as
 
 For strength level `4`, we used Python's `secrets` module to generate cryptographically secure passwords, ensuring the robustness and security of these passwords.
 
+#### Changelog:
+
+- v1.1: Doubled the amount of passwords. Now, there are 10.000.471 unique passwords.
+- v1.0: 5 Million unique passwords in 5 classes.
+
 ## Intended Uses
 
 - **Security Analysis**: PWLDS can be used to study common password patterns and weaknesses, helping to identify vulnerabilities and improve password policies.
@@ -32,6 +37,7 @@ For strength level `4`, we used Python's `secrets` module to generate cryptograp
 
 ## Limitations
 
+- **Exclusivity to English Words**: The password categories primarily utilize English words. Future versions may include support for other languages.
 - **No Real-World Data**: The dataset is synthetically generated and does not contain real user passwords. While this avoids privacy concerns, it may not fully represent real-world password distribution and usage patterns.
 - **Bias in Password Generation**: Since passwords are generated based on predefined rules and patterns, there may be biases that do not reflect the diversity of passwords used in real-life scenarios.
 - **Exclusivity to English Words**: The weak and very weak password categories rely heavily on English words, which may not be representative of non-English-speaking populations.