FINE-TUNING INDONESIAN QUESTION ANSWERING MODEL TRAINING WITH TENSOR PROCESSING UNIT
The research focuses on the application of fine tuning method and TPU within the process of training question answering (QA) for Bahasa Indonesia model. This method is chosen due to its effectiveness in speeding up the training time while still retaining high accuracy value. The research started...
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| Main Author: | |
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/74784 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | The research focuses on the application of fine tuning method and TPU within the
process of training question answering (QA) for Bahasa Indonesia model. This
method is chosen due to its effectiveness in speeding up the training time while
still retaining high accuracy value. The research started with exploring theories
about Transformers, BERT, distilBERT, and previous researches on question
answering models. The research continues with preprocessing the dataset and
building the model based on the hyperparameter tuning applied. The model is
then ready to be trained and evaluated. There are three metrics that has been
chosen to evaluate the model, such as accuracy, F1-Score, and exact match (EM).
The results of this experiment elaborated that by using fine-tuning and also with
the help of TPU, the model can achieve high accuracy within much faster time. It
is hoped that this research is able to serve as a stepping stone to future research
and development of question answering model, especially Indonesian question
answering. |
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