Update README.md

README.md

@@ -4,7 +4,7 @@ license: mit
 
 # Classifiers Enhanced by Pre-training
 
-This project utilizes a visual encoder from CLIP (ViT-B/32) to build image classifiers, enhanced by pre-training techniques. To use the trained models, follow the steps below to set up and run the classifiers.
+This project utilizes a visual encoder from the pre-trained CLIP (ViT-B/32) to build image classifiers. To use the trained models, follow the steps below to set up and run the classifiers.
 
 ## Prerequisites
 
@@ -12,12 +12,12 @@ Before you start, make sure you have Python and the necessary libraries installe
 
 ## Downloading Model Weights
 
-You need to download the following pre-trained model weights for running the `test.py` or `run_test.slurm`:
+You need to download the following trained model weights for running the `test.py` or `run_test.slurm`:
 - `fine-tune-best.pth`: Best model weights after fine-tuning.
 - `linear-probe-best.pth`: Best model weights after the linear probe training.
 - `train-from-scratch-best.pth`: Best model weights trained from scratch.
 
-Please download these files and place them in the `results/` directory within the project folder.
+Please download these files and place them under the `results/` directory within the project folder.
 
 ## Installation and Usage