Update README.md

README.md

@@ -23,15 +23,15 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 88.4
+      value: 56.2
       verified: false
     - name: Recall
       type: recall
-      value: 71.6
+      value: 65.8
       verified: false
     - name: F1 
       type: f1
-      value: 79.1
+      value: 60.6
       verified: false
   - task:
       type: text-generation
@@ -41,15 +41,15 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 65.3
+      value: 42.1
       verified: false
     - name: Recall
       type: recall
-      value: 62.7
+      value: 47.5
       verified: false
     - name: F1 
       type: f1
-      value: 63.9
+      value: 44.6
       verified: false
   - task:
       type: text-generation
@@ -59,15 +59,15 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 77.7
+      value: 38.6
       verified: false
     - name: Recall
       type: recall
-      value: 77.5
+      value: 56.0
       verified: false
     - name: F1 
       type: f1
-      value: 77.6
+      value: 45.7
       verified: false
   - task:
       type: text-generation
@@ -77,15 +77,15 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 69.5
+      value: 52.8
       verified: false
     - name: Recall
       type: recall
-      value: 46.0
+      value: 49.8
       verified: false
     - name: F1 
       type: f1
-      value: 55.3
+      value: 51.2
       verified: false
   - task:
       type: text-generation
@@ -131,7 +131,7 @@ model-index:
 ## Summary
 
 The model corrects spelling errors and typos in both Russian and English languages by bringing all the words in the text to the norm of the language.
-Corrector had been trained based on the model [FRED-T5-1.7B](https://huggingface.co/google/mt5-large) architecture. 
+Corrector had been trained based on the model [mT5-large](https://huggingface.co/google/mt5-large) architecture. 
 An extensive dataset with “artificial” errors was taken as a training corpus: the corpus was assembled on the basis of the Russian-language Wikipedia and transcripts of Russian-language videos, then typos and spelling errors were automatically introduced into it using the library [SAGE](https://github.com/ai-forever/sage).
 
 ## Public references
@@ -164,7 +164,8 @@ RUSpellRU, MultidomainGold, MedSpellChecker, GitHubTypoCorpusRu are datasets for
 **RUSpellRU**
 | Model | Precision | Recall | F1 | 
 | --- | --- | --- | --- | 
-| sage-mt5-large | 88.4 | 71.6 | 79.1 | 
+| sage-mt5-large | 56.2 | 65.8 | 60.6 | 
+| sage-mt5-large (ft.) | 88.4 | 71.6 | 79.1 | 
 | sage-ai-service | 93.5 | 82.4 | 87.6 | 
 | gpt-3.5-turbo | 39.6 | 62.3 | 48.5 | 
 | gpt-4 | 69.5 | 81.0 | 74.8 | 
@@ -172,7 +173,8 @@ RUSpellRU, MultidomainGold, MedSpellChecker, GitHubTypoCorpusRu are datasets for
 **MultidomainGold**
 | Model | Precision | Recall | F1 | 
 | --- | --- | --- | --- | 
-| sage-mt5-large | 65.3 | 62.7 | 63.9 | 
+| sage-mt5-large | 42.1 | 47.5 | 44.6 | 
+| sage-mt5-large (ft.) | 65.3 | 62.7 | 63.9 | 
 | sage-ai-service | 70.9 | 68.8 | 69.9 | 
 | gpt-3.5-turbo | 17.8 | 56.1 | 27.0 | 
 | gpt-4 | 31.1 | 78.1 | 44.5 | 
@@ -180,20 +182,39 @@ RUSpellRU, MultidomainGold, MedSpellChecker, GitHubTypoCorpusRu are datasets for
 **MedSpellChecker**
 | Model | Precision | Recall | F1 | 
 | --- | --- | --- | --- | 
-| sage-mt5-large | 77.7 | 77.5 | 77.6 | 
+| sage-mt5-large | 38.6 | 56.0 | 45.7 | 
+| sage-mt5-large (ft.) | 77.7 | 77.5 | 77.6 | 
 | sage-ai-service | 73.4 | 76.2 | 74.9 | 
 | gpt-3.5-turbo | 15.1 | 53.6 | 23.5 | 
 | gpt-4 | 48.9 | 88.7 | 63.1 | 
 
-
 **GitHubTypoCorpusRu**
 | Model | Precision | Recall | F1 | 
 | --- | --- | --- | --- | 
-| sage-mt5-large | 69.5 | 46.0 | 55.3 | 
+| sage-mt5-large | 52.8 | 49.8 | 51.2 | 
+| sage-mt5-large (ft.) | 69.5 | 46.0 | 55.3 | 
 | sage-ai-service | 76.1 | 51.2 | 61.2 | 
 | gpt-3.5-turbo | 23.7 | 43.9 | 30.8 | 
 | gpt-4 | 34.7  | 60.5 | 44.1| 
 
+**BEA60K**
+| Model | Precision | Recall | F1 |
+| --- | --- | --- | --- |
+| sage-mt5-large | 64.7 | 83.8 | 73.0 | 
+| gpt-3.5-turbo |  66.9 | 84.1 | 74.5 | 
+| gpt-4 | 68.6 | 85.2 | 76.0 | 
+| Bert (https://github.com/neuspell/neuspell) | 65.8 | 79.6 | 72.0 |
+| SC-LSTM (https://github.com/neuspell/neuspell) | 62.2 | 80.3 | 72.0 |
+
+**JFLEG**
+| Model | Precision | Recall | F1 |
+| --- | --- | --- | --- |
+| sage-mt5-large | 74.9 | 88.4 | 81.1 |
+| gpt-3.5-turbo |  77.8 | 88.6 | 82.9 | 
+| gpt-4 | 77.9 | 88.3 | 82.8 |
+| Bert (https://github.com/neuspell/neuspell) | 78.5 | 85.4 | 81.8 |
+| SC-LSTM (https://github.com/neuspell/neuspell) | 80.6 | 86.1 | 83.2 |
+
 
 ## How to use
 ```python