Update README.md

README.md

@@ -20,7 +20,7 @@ There are two models that we developed:
 RoSBERTa is based on [ai-forever/ru-en-RoSBERTa](https://huggingface.co/ai-forever/ru-en-RoSBERTa) with multiple heads for downstream tasks:
 - **Backbone**: Fully unfrozen, with the **NER head** fine-tuned for location recognition.
 - **Allocator head**: Trained to determine whether or not a message contains the actual location of the user.
-- **Adapter and tags head**: Trained to mark messages with different categories describing the message's context, such as tools, medicine, clothing, and more.
+- **Tags head with 1 layer of adapter**: Trained to mark messages with different categories describing the message's context, such as tools, medicine, clothing, and more.
 
 ### [rubert-tiny-separater](https://huggingface.co/poc-embeddings/rubert-tiny-separater)
 Rubert is based on [sergeyzh/rubert-tiny-turbo](https://huggingface.co/sergeyzh/rubert-tiny-turbo) with a linear layer on top. The whole model was trained for classifying message types from Telegram marketplaces.