Update README.md

README.md

@@ -7,15 +7,15 @@ tags:
 pipeline_tag: text-classification
 ---
 # Model description
-**PPPSL-ESM2**(PPPSL, Prediction of prokaryotic protein subcellular localization) is a protein language model fine-tuned from [**ESM2**](https://github.com/facebookresearch/esm) pretrained model [(***facebook/esm2_t36_3B_UR50D***)](https://huggingface.co/facebook/esm2_t36_3B_UR50D) on a prokaryotic protein subcellular localization dataset.   
+**PPPSL**(PPPSL, Prediction of prokaryotic protein subcellular localization) is a protein language model fine-tuned from [**ESM2**](https://github.com/facebookresearch/esm) pretrained model [(***facebook/esm2_t36_3B_UR50D***)](https://huggingface.co/facebook/esm2_t36_3B_UR50D) on a prokaryotic protein subcellular localization dataset.   
 
-**PPPSL-ESM2** achieved the following results:  
+**PPPSL** achieved the following results:  
 Train Loss: 0.0148  
 Train Accuracy: 0.9923  
 Validation Loss: 0.0718  
 Validation Accuracy: 0.9893  
 Epoch: 20 
-# The dataset for training **PPPSL-ESM2**
+# The dataset for training **PPPSL**
 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.  
 
@@ -24,7 +24,7 @@ The dataset was downloaded from the website at [**DeepLocPro - 1.0**](https://se
 # Model training code at GitHub
 https://github.com/pengsihua2023/PPPSL-ESM2
 
-# How to use **PPPSL-ESM2**
+# How to use **PPPSL**
 ### An example
 Pytorch and transformers libraries should be installed in your system.  
 ### Install pytorch