Update app.py

app.py

@@ -49,6 +49,12 @@ Our models are based on [BERTIN](https://huggingface.co/bertin-project). We fine
 
 Models showcased in the demo are marked with (*) above. More details about how we trained these models can be found in our [report](https://wandb.ai/readability-es/readability-es/reports/Texts-Readability-Analysis-for-Spanish--VmlldzoxNzU2MDUx).
 
+## Final Remarks
+
+- **Data.** One of the main challenges in the area of Automatic Readability Assessment is the availability of reliable data. For Spanish, in particular, the highest-quality existing dataset is Newsela. However, it has a restrictive license that prohibits publicly-sharing its texts. In addition, since its texts are translations from original English news, they can suffer from [translationese](https://en.wiktionary.org/wiki/translationese) deeming them less suitable for training models that will analyse texts produced directly in Spanish. Therefore, our first challenge was to find texts that were originally written in Spanish *and* that contain information about their readability level. Unfortunately, we could not find any other big publicly-available corpus, and decided to combine texts scraped from several webpages. This also prevented us for developing models that could estimate readability in more fine-grained levels (e.g. CEFR levels), which was our original goal. Future work includes contacting editorial groups (similar to Newsela) that create texts for learners of Spanish as a second language, and attempt to establish collaborations that could result in creating new language resources for the readability research community.
+
+- **Models.** 
+
 ### Team
 
 - [Laura Vásquez-Rodríguez](https://lmvasque.github.io/)