Update README.md

README.md

@@ -13,9 +13,9 @@ Our findings reveal a substantial improvement in scoring accuracy with G-SciEdBE
 which is trained to enhance the accuracy of automated scoring, offering a substantial contribution to the field of AI in education.
 
 ## Dataset
-It is a pre-trained German science education BERT for written German science assessments of PISA test.
+It is a pre-trained German science education BERT for written German science assessments of the PISA test.
 PISA is an international test to monitor education trends led by OECD (Organisation for Economic Co-operation and Development).
-PISA items are developed to assess scientific literacy, highlighting real-world problem-solving skills and the need of future workforce.
+PISA items are developed to assess scientific literacy, highlighting real-world problem-solving skills and the needs of future workforce.
 This study analyzed data collected for 59 construct response science assessment items in German at the middle school level. 
 A total of 6,116 German students from 257 schools participated in PISA 2015.
 Given the geographical diversity of participants, PISA data reflect the general German students' science literacy.
@@ -27,6 +27,10 @@ which means approximately 1,000 human-scored student responses per item for cont
 More than 10 human raters scored each response in the training dataset organized by OECD.
 The responses were graded irrespective of the student's ethnicity, race, or gender to ensure fairness.
 
+## Architecture
+The model is pre-trained on [G-BERT](https://huggingface.co/dbmdz/bert-base-german-uncased?text=Ich+mag+dich.+Ich+liebe+%5BMASK%5D) and the pre-trainig method can be seen as:
+![architecture](https://huggingface.co/ai4stem-uga/G-SciEdBERT/architecture.png)
+
 ## Usage
 
 With Transformers >= 2.3 our German BERT models can be loaded like this: