Update README.md

README.md

@@ -123,13 +123,11 @@ and detection. The datasets are challenging for most AI models and by being proc
 benchmark can be regenerated ad infinitum to create new test sets to combat the effects of models being trained
 on this data and the results being due to memorization.
 
-This dataset has 4 sub-tasks: Object Recognition, Visual Prompting. Spatial Rea-
-soning, and Object Detection. 
+This dataset has 4 sub-tasks: Object Recognition, Visual Prompting. Spatial Reasoning, and Object Detection. 
 
 For each sub-task, the images consist of images of pasted objects on random
 images. The objects are from the COCO object list and are gathered from internet data. Each object is
-masked using the DeepLabV3 object detection model and then pasted on a random background from the
-Places365 dataset.  The objects are pasted in one of four locations, top, left, bottom, and right, with small
+masked using the DeepLabV3 object detection model and then pasted on a random background.  The objects are pasted in one of four locations, top, left, bottom, and right, with small
 amounts of random rotation, positional jitter, and scale.
 
 There are 2 conditions “ single” and “ pairs”, for images with one and two objects. Each test set uses 20