Update README.md

README.md

@@ -28,7 +28,18 @@ An extensive dataset with “artificial” errors was taken as a training corpus
 ### Quality
 Below are automatic metrics for determining the correctness of the spell checkers. 
 We compare our solution with both open automatic spell checkers and the ChatGPT family of models on all four available datasets:
-- **RUSpellRU**: ****texts collected from ([LiveJournal](https://www.livejournal.com/media)), with manually corrected typos and errors;
+- **RUSpellRU**: texts collected from ([LiveJournal](https://www.livejournal.com/media)), with manually corrected typos and errors;
 - **MultidomainGold**: examples from 7 text sources, including the open web, news, social media, reviews, subtitles, policy documents and literary works;
 - **MedSpellChecker**: texts with errors from medical anamnesis;
 - **GitHubTypoCorpusRu**: spelling errors and typos in commits from [GitHub](https://github.com);
+
+**RUSpellRU**
+| Model | Precision | Recall | F1 |
+| --- | --- | --- | --- |
+| M2M100-1.2B | 59.4 | 43.3 | 50.1 |
+| ChatGPT gpt-3.5-turbo-0301 | 55.8 | 75.3 | 64.1 |
+| ChatGPT gpt-4-0314 | 57.0 | 75.9 | 63.9 |
+| ChatGPT text-davinci-003 | 55.9 | 75.3 | 64.2 |
+| Yandex.Speller | 83.0 | 59.8 | 69.5 |
+| JamSpell | 42.1 | 32.8 | 36.9 |
+| HunSpell | 31.3 | 34.9 | 33.0 |