Update README.md

README.md

@@ -52,11 +52,6 @@ outputs = model(**inputs)
 | Layers               | 6                                    |
 | Attention Heads      | 6                                    |
 
-### Intended Use
-
-**Intended Use Cases:** ProkBERT-mini-k6-s1 is intended for bioinformatics researchers and practitioners focusing on genomic sequence analysis, including:
-- sequence classification tasks
-- Exploration of genomic patterns and features
 
 ## Segmentation and Tokenization in ProkBERT Models
 
@@ -140,7 +135,17 @@ except ImportError:
 | iPromoter-BnCNN       | 0.55     | 0.27  | **0.99**    | 0.18        |
 | MULTiPly              | 0.54     | 0.19  | 0.92        | 0.22        |
 
-*The ProkBERT family models exhibit remarkably consistent performance across the metrics assessed. With respect to accuracy, all three tools achieve an impressive score of 0.87, marking them among the top performers in promoter prediction. This suggests that, regardless of the specific version, the underlying methodology used in the mini series is robust and effective.*
+*The ProkBERT family models exhibit remarkably consistent performance across the metrics assessed. With respect to accuracy, all three tools achieve an impressive*
+
+| Metric       | ProkBERT-mini | ProkBERT-mini-c | ProkBERT-mini-long | Promotech | Sigma70Pred | iPromoter-BnCNN | MULTiPly |
+|--------------|---------------|-----------------|--------------------|-----------|-------------|-----------------|----------|
+| Accuracy     | 0.81          | 0.79            | 0.81               | 0.61      | 0.62        | 0.61            | 0.58     |
+| F1           | 0.81          | 0.78            | 0.81               | 0.43      | 0.58        | 0.65            | 0.58     |
+| MCC          | 0.63          | 0.57            | 0.62               | 0.29      | 0.24        | 0.21            | 0.16     |
+| Sensitivity  | 0.81          | 0.75            | 0.79               | 0.29      | 0.52        | 0.66            | 0.57     |
+| Specificity  | 0.82          | 0.82            | 0.83               | 0.93      | 0.71        | 0.55            | 0.59     |
+
+*Promoter prediction performance metrics on a diverse test set. A comparative analysis of various promoter prediction tools, showcasing their performance across key metrics including accuracy, F1 score, MCC, sensitivity, and specificity.*