added f1 score

README.md

@@ -19,7 +19,11 @@ This model is trained to predict whether two given messages from some group chat
 # Training details
 
 It's based on [Conversational RuBERT](https://docs.deeppavlov.ai/en/master/features/models/bert.html) (cased, 12-layer, 768-hidden, 12-heads, 180M parameters) that was trained on several social media datasets. We fine-tuned it with the data from several Telegram chats. The positive `reply_to` examples were obtained by natural user annotation. The negative ones were obtained by shuffling the messages. 
-The task perfectly aligns with the Next Sentence Prediction task, so the fine-tuning was done in that manner. See the [paper](https://www.dialog-21.ru/media/5871/buyanoviplusetal046.pdf) for more details.
+The task perfectly aligns with the Next Sentence Prediction task, so the fine-tuning was done in that manner. 
+
+It achieves the 0.83 F1 score on the gold test set from our reply recovery dataset.
+
+See the [paper](https://www.dialog-21.ru/media/5871/buyanoviplusetal046.pdf) for more details.
 
 # Usage