doc: Updated the followup-notes files with notes taken locally

followup-notes.md

@@ -14,6 +14,43 @@
 
 ### Questions
 
+- Any recommendations on vectorizing the sentences ?
+- Should we go for character or word based vectorization ?
+
 ### Answers
 
+- A good start would be with word based vectorization it's simpler and involves less dimensions
+
+### Remarks
+
+Our idea to train and compare different models seems interesting to Prof. Nassar and he would like to see an F1-score comparison chart.
+
+## Follow up 2
+
+**Date:** Friday 29 November 2024
+
+### Work done
+
+- HMM
+- Trained and evaluated LSTM
+- Trained and evaluated BiLTM
+- Starting to train BERT
+
 ### Remarks
+
+Prof. Nassar said to use `cmarkea/distilcamembert-base` instead of `camembert-base` because it converges faster.
+
+## Follow up 3
+
+**Date:** Friday 17 January 2025
+
+### Work done
+
+- Trained and evaluated CamemBERT
+- Tested and evaluated LSTM and BiLSTM with POS as extra features
+- Modified the interface to include a selected for the model
+- Refactored the interface and added tabs for files with multiple sentences
+
+### Remarks
+
+Prof. Nassar was happy with our work and excited to see the final product on the keynote.