Update README.md

README.md

@@ -1,26 +1,60 @@
----
-license: cc-by-4.0
-dataset_info:
-  features:
-  - name: folder
-    dtype: string
-  - name: title
-    dtype: string
-  - name: text
-    dtype: string
-  - name: title_len
-    dtype: int64
-  - name: text_len
-    dtype: int64
-  splits:
-  - name: train
-    num_bytes: 1126829322
-    num_examples: 512750
-  download_size: 590025488
-  dataset_size: 1126829322
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
----
+---
+license: cc-by-4.0
+dataset_info:
+  features:
+  - name: folder
+    dtype: string
+  - name: title
+    dtype: string
+  - name: text
+    dtype: string
+  - name: title_len
+    dtype: int64
+  - name: text_len
+    dtype: int64
+  splits:
+  - name: train
+    num_bytes: 1126829322
+    num_examples: 512750
+  download_size: 590025488
+  dataset_size: 1126829322
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+---
+
+This is an Uzbek News Dataset with 512,750 articles (120 million words and in the Latin script) scraped from the web in 2023. 
+
+I combined and uploaded the dataset in this HF repo so that the community can fine-tune LLMs based on the Uzbek language.
+
+---
+
+
+
+```
+@proceedings{kuriyozov_elmurod_2023_7677431,
+  title        = {{Text classification dataset and analysis for Uzbek 
+                   language}},
+  year         = 2023,
+  publisher    = {Zenodo},
+  month        = feb,
+  doi          = {10.5281/zenodo.7677431},
+  url          = {https://doi.org/10.5281/zenodo.7677431}
+}
+```
+
+Github: [github](https://github.com/elmurod1202/TextClassification) 
+Arxiv: https://arxiv.org/ftp/arxiv/papers/2302/2302.14494.pdf
+
+Original dataset was created by scraping the Internet.
+
+
+From the authors:
+
+
+The dataset consists text data from 9 Uzbek news websites and press portals that included news articles and press releases. 
+These websites were selected to cover various categories such as politics, sports, entertainment, technology, and others. 
+In total, we collected 512,750 articles with over 120 million words accross 15 distinct categories, which provides a large and diverse corpus for text classification.
+It is worth noting that all the text in the corpus is written in the Latin script.