Update README.md

README.md

@@ -3,6 +3,10 @@ license: apache-2.0
 base_model: sentence-transformers/LaBSE
 tags:
 - generated_from_trainer
+- news
+- russian
+- media
+- text-classification
 metrics:
 - accuracy
 - f1
@@ -14,6 +18,13 @@ model-index:
 datasets:
 - data-silence/rus_news_classifier
 pipeline_tag: text-classification
+language:
+- ru
+widgets:
+- text: "Введите новостной текст для классификации"
+  example_title: "Классификация новостей"
+  button_text: "Классифицировать"
+  api_name: "classify"
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -21,7 +32,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 # news_classifier_ft
 
-This model is a fine-tuned version of [sentence-transformers/LaBSE](https://huggingface.co/sentence-transformers/LaBSE) on an unknown dataset.
+This model is a fine-tuned version of [sentence-transformers/LaBSE](https://huggingface.co/sentence-transformers/LaBSE) on my rus-news-classifier dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.3820
 - Accuracy: 0.9029
@@ -31,11 +42,22 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+This is a multi-class classifier of Russian news, made with the LaBSE model finetune. The news category is assigned by the classifier to one of 11 categories:
+- climate (климат)
+- conflicts (конфликты)
+- culture (культура)
+- economy (экономика)
+- gloss (глянец)
+- health (здоровье)
+- politics (политика)
+- science (наука)
+- society (общество)
+- sports (спорт)
+- travel (путешествия)
 
 ## Intended uses & limitations
 
-More information needed
+Enjoy to use in your purpose
 
 ## Training and evaluation data