Update README.md

README.md

@@ -7,16 +7,16 @@ tags:
 pipeline_tag: text-classification
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 # Model descriptions
-PPPSL-ESM2(PPPSL, Prediction of prokaryotic protein subcellular localization) is a protein language model fine-tuned from ESM2 pretrained model [facebook/esm2_t36_3B_UR50D](https://huggingface.co/facebook/esm2_t36_3B_UR50D) on a prokaryotic protein subcellular localization dataset. It achieves the following results on the evaluation set:  
+**PPPSL-ESM2**(PPPSL, Prediction of prokaryotic protein subcellular localization) is a protein language model fine-tuned from ESM2 pretrained model [facebook/esm2_t36_3B_UR50D](https://huggingface.co/facebook/esm2_t36_3B_UR50D) on a prokaryotic protein subcellular localization dataset. It achieves the following results:  
 Train Loss: 0.0015  
 Train Accuracy: 0.9893  
 Validation Loss: 0.0155  
 Validation Accuracy: 0.9702  
 Epoch: 20 
-# The dataset for training PPPSL-ESM2
+# The dataset for training **PPPSL-ESM2**
 The full dataset contains 11,970 protein sequences, including Cellwall (87), Cytoplasmic (6,905), CYtoplasmic Membrane (2,567), Extracellular (1,085), Outer Membrane (758), and Periplasmic (568).
 The highly imbalanced sample sizes across the six categories in this dataset pose a significant challenge for classification.  
-# How to use
+# How to use **PPPSL-ESM2**
 
 ### An example
 Pytorch and transformers libraries should be installed in your system.