Update README.md

README.md

@@ -9,7 +9,7 @@ metrics:
 
 ## Model description
 
-This  2dCNNmsda model is a two-dimensional convolutional neural network  (2D-CNN) architecture trained from scratch on Sentiment Analysis for Social Media Posts in Arabic Dialect (MSDA) dataset with three window sizes of 3, 4, and 5, and 100 filters for each window size.
+This  2dCNNmsda model is a two-dimensional Convolutional Neural Network (2D-CNN) architecture trained from scratch on Sentiment Analysis for Social Media Posts in Arabic Dialect (MSDA) dataset with three window sizes of 3, 4, and 5, and 100 filters for each window size.
 It achieves the following results on the evaluation test set:
  - Accuracy: 77%
 
@@ -29,7 +29,7 @@ It achieves the following results on the evaluation test set:
 
 ## Training and evaluation data
 
-We trained this model on a 90% train set and evaluated it on a 10% test set.
+We trained this model on a 90% training set and evaluated it on a 10% testing set.
 
 ## Training procedure
 We have trained this model using the Paperspace GPU-Cloud service. We used a machine with 8 CPUs, 45GB RAM, and A6000 GPU with 48GB RAM.