T2E Vocabulary Exam Generator as the name suggest, is an open souce program that allows user, in this case being teachers, to generate English vocabulary exam right from their browser. We aim to help reduce the pain point of teacher having to spend his/her/their precious time and effort to make the entire vocabulary exam or quiz. To try it out, click the Demo link in the Quick Links section below.
This readme.md file is an explanation of this folder that it's in.
- Demo: https://huggingface.co/spaces/nontGcob/T2E_Vocabulary_Exam_Generator
- Documentation: https://mario-world.medium.com/text-to-exam-generator-nlp-using-machine-learning-71da8dd93a4a
- Exploratory_Data_Analysis.ipynb
- This code runs through the entire dataset that we have and analyse the part of speech of all the lexical vocabulary, the max/min/average vocabulary length, and the number of times a word is presented
- Test_&Fine_tune&_Retest.ipynb
- This code tests the accuracy of the pre-trained model which is our baseline. It fine-tunes the model. And then, it tests the fine-tuned model again to check whether the accuracy has increased or not.
- Error_Analysis.ipynb
- This code analyses the prediction by analysing the type number of correct and wrong vocabulary predictions, the types of the part of speech of the correct and wrong vocab predictions, and the average vocabulary length of the correct and wrong vocab predictions.
Please keep in mind that in order to run the .ipynb file in this folder, you must also download the "simple_trained_wsd_pipeline" and "semcor_samples_4-samples.json" as well which are not included in the folder due to the file size limitation of the code that can be uploaded to GitHub. For more information and the explanation of the entire process of this machine learning project, visit the Documentation link that is attached above in the Quick Links section.
- Name: Nutnornont Chamadol
- Email: nontc49@gmail.com
- Visit my personal website https://nontgcob.com/ to learn more about me.
Copyright (c) 2023 Nutnornont Chamadol
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