Update README.md

README.md

@@ -45,7 +45,7 @@ We used `PyTorchBenchmark` from `transformers` to evaluate model's performance a
 | **distilrubert-tiny-cased-conversational** | 16 | 512  |  **0.219** | **0.003**  | **633**  | **1291** |
 
 
-To evaluate model quality, we fine-tuned DistilRuBERT-small on classification (RuSentiment, ParaPhraser), NER and question answering data sets for Russian and obtained scores very similar to the [Conversational DistilRuBERT-small](https://huggingface.co/DeepPavlov/distilrubert-small-cased-conversational). 
+To evaluate model quality, we fine-tuned DistilRuBERT-tiny on classification (RuSentiment, ParaPhraser), NER and question answering data sets for Russian and obtained scores very similar to the [Conversational DistilRuBERT-small](https://huggingface.co/DeepPavlov/distilrubert-small-cased-conversational). 
 
 \[1\]: P. Lison and J. Tiedemann, 2016, OpenSubtitles2016: Extracting Large Parallel Corpora from Movie and TV Subtitles. In Proceedings of the 10th International Conference on Language Resources and Evaluation \(LREC 2016\)