fix some typos and add final mark

README.md

@@ -1,18 +1,29 @@
+<!-- omit in toc -->
+# TOC
+- [Language Modelling](#language-modelling)
+  - [Project description](#project-description)
+  - [Results](#results)
+  - [Final Mark](#final-mark)
+
 # Language Modelling
 Repository containing the results of the Natural Language Understanding course project about Language Modelling.
 
 ## Project description
 The proposed task of Language Modelling (LM) for the NLU course required to:
 
 1. implement a Language Model using one of the RNN architectures (eg. Vanilla, LSTM, GRU);
-2. train it and evaluate its performance on the word-level Penn Treebank (PTB) dataset; 
+2. train it and evaluate its performance on the word-level Penn Treebank (PTB) dataset;
 3. reach a baseline value of 140 PP using a Vanilla RNN, or 90.7 PP using an LSTM.
 
+## Results
 As a starting point, I decided to implement a very basic model made of:
 - a neural embedding layer;
 - an LSTM, to capture context information;
 - a fully connected layer, for the final word prediction; and obtained 137 PP.
 
 To improve such results, I have considered the techniques described by Merity et. al, reaching 81.43 PP.
 
-![](./report/assets/run_results_best.png)
+![](./report/assets/run_results_best.png)
+
+## Final Mark
+The Examination Board gave me a full mark for my project (**30 Cum Laude**).