Update README.md

README.md

@@ -1,15 +1,23 @@
 ---
 license: apache-2.0
 ---
+# Classifier architecture
+The classifier uses DenseNet161 as the encoder and some linear layers at classifier base. 
+
+# Model accuracy:
+Model achieves 91.3% accuracy on the validation set.
+
+
+
 # Training dataset metadata:
 1. Dataset classes: ['soft', 'digital', 'hard']
 2. Number of classes: 3
 3. Total number of images: 18415
-## Number of images per class:
+# Number of images per class:
  - soft : 5482
  - digital : 1206
  - hard : 11727
-## Classes description:
+# Classes description:
 1. The **hard** class denotes a group of scenes to which a coarser background removal method should be applied, intended for objects with an edge without small details.
 The hard class contains the following categories of objects:
 object, laptop, charger, pc mouse, pc, rocks, table, bed, box, sneakers, ship, wire, guitar, fork, spoon, plate, keyboard, car, bus, screwdriver, ball, door, flower, clocks, fruit , food, robot.
@@ -20,6 +28,3 @@ animal, people, human, man, woman, t-shirt, hairs, hair, dog, cat, monkey, cow,
 3. The **digital** class denotes a group of images with digital graphics, such as screenshots, logos, and so on.
 The digital class contains the following categories of scenes:
 screenshot
-
-## Architecture
-The classifier uses DenseNet161 as the encoder and some linear layers at classifier base.